techno –economic assessment of carbon capture and storage...

Techno-economic assessment of carbon capture and storage deployment in power stations in the Southern African and Balkan regions Mario Tot, Damir Pešut, EIHP Alison Hudges, Catherine Fedorski, Bruno Merven, Ajay Trikam, University of Cape Town Jan Duerinck, Helga Ferket, Arnoud Lust, VITO Study accomplished under the authority of the World Bank TEM/N93Q6/2011-0005 May 2011

This report was prepared as a background paper for the World Bank report Carbon Capture and Storage in Developing Countries: A Perspective on Barriers to Deployment, 2011 (available at: http://go.worldbank.org/MJIX0TRAB0). The research was conducted by VITO, The University of Cape Town Energy Research Centre and Energetski Institute Hrvoje Pozar (EIHP) on behalf of the World Bank Group. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of the World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.

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SUMMARY

In this study, a techno-economic modelling excercise was carried out to investigate the effect of several climate policies on the power sectors of the Balkans and Southern Africa, examining in particular their effect on the deployment of carbon capture and storage technologies. What is carbon capture and storage? Carbon capture and storage (CCS) is a technology for separation and sequestration of CO2

emissions from the flue gasses of burning fossil fuels or biomass and it is likely to become one of the most promising technological solutions for achieving stringent CO2 emissions reductions in the atmosphere in the next 20 years. CCS in the electricity sector involves capturing of CO2 in electricity plants, transport of the CO2 by pipeline or other means, and its storage in suitable geological formations. For capturing of CO2, different technological options exist, which can be classified into three technology groups: (1) Post-combustion capturing is an operational technology at the industry level, but it is actually not yet exploited at the scale required to have a significant impact on the CO2 emissions of the electricity sector. CO2 emissions are removed from the flue gasses by a solvent and pure CO2 is produced when regenerating the solvent. (2) In the pre-combustion technology, H2 is produced from traditional fuels, and CO2 is removed before burning. (3) In the oxi-fuel technology fuels are burned by pure oxygen in the absence of N2.The flue gasses contain a mixture of H2O and CO2 which are easily separated by condensing. Transport of CO2 can be done by pipeline, ship, train or truck and is a mature technology. Given the volumes that need to be transported, pipeline transport seems the most economic solution, and is considered much less costly than the CO2 capturing and storage components of an integrated CCS system. For storage of CO2 four types of geological formations are considered. (1) Depleted oil and gas fields: The characteristics of these formations (size, depth, injectivity) are well known from industry activities in oil and gas exploration. Often, parts of the infrastructure for oil or gas production can be reused, making this type of storage option interesting from an economical point of view. The disadvantage is that these formations usually are not very large. An important issue is also that the use or lose principle applies, since storage of CO2 should start within a short time frame of pumping oil or gas, so as to avoid degradation to the wells that occur over time. (2) Saline aquifers: These are underground formations filled with salt water. At present, about 1 Mton CO2 is injected yearly in a saline formation which is located above the Sleipner off-shore gas field close to Norway. (3) Enhanced oil recovery (EOR): This is an option in nearly depleted oil fields. CO2 is injected into the rock formations to drive out the residual oil. Recuperated oil generates extra revenue, making EOR an economical beneficial option. EOR is a mature technology and is applied in different locations across the globe. For gasfields, the equivalent technology is Enhanced gas recovery (EGR). (4) Enhanced coal bed methane recovery (ECBM): Coal layers at depths of 800 m and more that cannot be exploited economically contain considerable amounts of methane that can be released and recovered by injecting CO2 into the coal layers. At present, ECBM is not yet fully commercially exploited. In the Allison Unit CO2 ECBM pilot project, CO2 has been injected into the San Juan basin in southern US since 1995.

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Exploration of suitable geological storage options in the Balkan region and in the South African region Identification of suitable geological formations has been carried out through an extensive literature review. The results of the data collection and analysis phase are summarized in a reservoir matrix for each region. These tables contain the potential storage options, give the known reservoir characteristics, outline the uncertainties and exploration needs, specify the bottlenecks, indicate the time of availability for a certain option and report the used references. These tables can be updated in the future when more exploration data become available. The options are classified using a colour code. Red signifies “not an option”, orange is for “might be possible, but requires fundamental exploration before capacity can be confirmed”, yellow means “possible, but major exploration required”, and green is “possible with limited exploration efforts required”. The colours do not refer to economic feasibility. The reservoir options in green and yellow have been considered explicitly as possible storage options for the modeling exercise, and the non-economic options within this subgroup have been excluded. The economic conditions for different types of geological formations have been quantified based on a life cycle approach. The life-cycle of a storage project (Figure 32) encompasses the (1) pre-injection phase where further exploration and/or site characterization need to be performed; (2) the development phase with drilling, completion and testing; (3) the injection phase with operational costs and regular / continuous monitoring; (4) the post-closure period where monitoring is persisted with until permanent containment is proven and transfer can be considered;, and finally (5) the post-transfer or abandonment stage where responsibility is passed over to the competent authorities. Conclusions from the geological analysis Country specific information of suitable storage locations is given in Annex A. The large capacity storage options (Gton range) are to be found in saline aquifers. The aquifers in sedimentary basins are not sufficiently characterized at present. In all the investigated countries there is a lack of data to allow for reliable quantitative estimates of such storage capacity. The best opportunities for saline aquifer storage are linked to hydrocarbon prospects (e.g. an aquifer below an oil/gas field, or an aquifer within a petroleum basin that might contain undiscovered hydrocarbon reserves) and hence require collaboration with the petroleum industry. Storage in mature or depleted oil and gas fields could be combined with the economic benefit of EOR or EGR and with the presence of infrastructure and detailed exploration data. However, (1) the capacity of individual fields is limited (in the order of a few Mton to a few tens of Mton CO2 for the largest known fields); and (2) timing is crucial since the “use or lose” rule can be applied. Cost functions, expressing the unit storage costs as a function of the potential storage size have been estimated for typical geological formations. Storage unit costs primarily depend on the size of the project as well as on the daily injection rate. Higher injection rates are more expensive as more injection wells are required. Life cycle unit storage costs are estimated in the range 5-10 USD/ton CO2 for larger projects starting at 20 Mton in saline aquifers. For depleted oil and gas fields, the figures are somewhat lower due to the fact that the existing infrastructure can be recovered. For EOR a benefit of 40 USD/ton CO2 has been calculated from the enhanced oil production, largely offsetting storage costs. For ECBM, storage cost depends on injectivity of the

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coal. For a high injectivity, costs are in the range 3-5 USD/ton. The benefits from methane recovery have been quantified at 4.8 USD/ton CO2. Scenario analysis based on the techno economic optimisation model MESSAGE Characteristics of electricity generation and consumption are well represented in techno-economic optimisation models, that can account for the fact that 1) many different production technologies exist, competing with each other; 2) electricity production plants have a lifetime of 25 to 45 years, depending on the technology; and 3) assuming there is no electricity storage in the system, electricity production is always for immediate consumption, i.e. the supply must follow fluctuations in demand. The basic methodology in techno-economic optimisation models is that the total costs for the production of the electricity, determined by a given electricity demand scenario, are minimized. Future costs are discounted using a discount factor. This analysis uses a discount factor of 8%. The models can be used to examine various climate policies. For this study, the MESSAGE model has been chosen to perform scenario analysis for a period 2010 - 2030. The following scenarios have been developed:

Reference or least cost scenario (with and without EOR options): In this scenario no additional constraints or CO2 prices have been imposed

Efficiency scenario: The objective of this scenario is quantifying the effect of an energy efficiency policy on the CO2 emissions of the electricity sector. This has been explored only for the Balkan region, as such a policy is not clearly defined and quantified in the Southern African region.

Base-line scenario: The scenario takes into account decided policies and planned expansion of the electricity production units.

Renwable Electricity Standard (RES) scenario: Analyses the potential of increased construction of renewable technologies, including large hydro, wind, thermal solar, and solar PV.

CO2 price scenario: Price levels of 25, 50, and 100 USD/ton CO2 have been investigated using the model.

CO2 limit scenario: A constraint on the CO2 emissions of 10% and 20% in 2030 compared to the reference scenario, has been investigated in the model.

CCS target: For this scenario, the implementation CCS up to a certain level has been imposed as a constraint.

The specifics of each scenario are particular to the Balkan and the Southern African regions, such that the assumptions and variations on the scenarios have been chosen to better reflect the local circumstances. Results The Balkan region In the reference scenario CCS is not a competitive technology unless the benefits of EOR are accounted for. With the EOR options included in the model, 97.4 Mton CO2 is stored. CCS is not competitive against other alternatives in the base line, renewable energy and efficiency scenarios. When implementing a carbon price, CCS starts to become competitive when a CO2 price of 50 USD is imposed. It is most competitive in Kosovo due to the low cost of coal development. The share of CCS in 2030 amounts to 10.2% in 2030. In the higher CO2 price scenarios CCS becomes fully competitive both for new plants and as a retrofit option in existing plants. The results of the CO2 limit scenario depend on whether nuclear power is available as an alternative. If nuclear power is

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modelled as an option, then CCS is hardly developed, but when the nuclear option is excluded then CCS becomes competitive to achieve the targets. The scenarios results for CO2 emissions and the average cost of electricity are illustrated in the figures below. Emissions in the reference scenario, the baseline scenario, the efficiency scenario and the renewable scenario are all in the range of a few percentage points. Larger reductions are achieved by limiting the emissions, or by introducing an CO2 price. The lowest CO2 emissions are achieved in the scenario with a carbon price of 100 USD/ton, followed by the 50 USD /ton CO2 scenario.

Figure 1: Comparison of total CO2 emission across scenarios for the Balkan region

The highest average generation costs for electricity are obtained when a price of 100 USD is imposed (note that this price is included in the costs reported1). This explains why the cost of the scenario with a limit of 20% and a price of 25 USD/ton CO2 is significantly higher compared to the normal 20% limit scenario without the carbon price.

1 From a social point of view a carbon price or a tax should not be considerd as a cost but as a transfer of

wealth to government. From a private point of view the carbon price is considered as a cost.

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Figure 2: Comparison of average generation costs across scenarios for the Balkan region

The Southern African region In the reference scenario, CCS technologies are not competitive. In the baseline scenario a CO2 limit of 275 Mton of CO2 has been imposed as per South Africa’s Integrated Resource Plan (IRP). The baseline without accounting for EOR/ECBM benefits results in a small penetration of CCS in gas fired plants. In the baseline with EOR/ECBM benefits there is also a small amount of retrofit with CCS installed on South African coal plants and CO2 is exported to depleted oil/gas fields in Mozambique towards the end of the study horizon. In the scenario with 25 USD/ton CO2 price the share of CCS increases to 10% by 2030. This share increases to 12% in the scenario with 50 USD/ton CO2 and to 15% in the scenario with 100 USD/ton CO2. So, contrary to the Balkan results we do not see a massive penetration of CCS technologies when a high CO2 price is imposed. The reason for this is that, due to the absence of water, coal plants in the Southern African region are air cooled, resulting in lower efficiencies. As CCS results in an additional loss of efficiency (in terms of overall net plant output to the grid due to the parasitic load), the penalty becomes too high. The CO2 emissions and the average reduction costs across the scenarios for the Southern African region are presented in the figures below. Note that the significant drop in the CO2 emissions in the 100 USD/ton CO2 price scenario is only partly explained by CCS. In this scenario there is also a strong increase of nuclear and renewable energies that contributes to the emission reduction.

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Figure 3: Comparison of total CO2 emission across the scenarios for the Southern African region

Figure 4: Comparison of average generation costs including CO2 price across scenarios for the Southern African Region

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TABLE OF CONTENTS

CHAPTER 1 MEthodology and structure ___________________________________________ 21

1.1. Introduction 21

1.2. Methodology of techno-economic optimization models 21

CHAPTER 2 Regional overviews __________________________________________________ 24

2.1. Balkan region 24 2.1.1. Energy community __________________________________________________ 24 2.1.2. Main development indicators __________________________________________ 26 2.1.3. Installed generation capacity in Balkan region – summary ___________________ 27 2.1.4. Electricity consumption, production and exchange in Balkan region – summary __ 28 2.1.5. Power transmission network in Balkan region – summary ____________________ 29 2.1.6. Electricity demand in Balkan region up to 2030 ____________________________ 31 2.1.7. Power generation expansion possibilities in Balkan region – summary __________ 32 2.1.8. CO2 emission sources from power generation in Balkan region – summary ______ 34

2.2. Country case studies - Balkan region 38 2.2.1. Croatia ____________________________________________________________ 38 2.2.2. Bosnia and Herzegovina ______________________________________________ 40 2.2.3. Serbia _____________________________________________________________ 44 2.2.4. Kosovo ____________________________________________________________ 47 2.2.5. Montenegro _______________________________________________________ 50 2.2.6. Albania ____________________________________________________________ 52 2.2.7. Macedonia _________________________________________________________ 56

2.3. Southern African region 58 2.3.1 Background: The Southern African Power Pool ____________________________ 59 2.3.2 Main development indicators __________________________________________ 60 2.3.3 Installed generation capacity – summary _________________________________ 60 2.3.4 Electricity consumption, production and exchange in the Southern African region - summary 61 2.3.5 Power transmission network in the region – summary ______________________ 61 2.3.6 Electricity consumption in the Southern African region up to 2030 ____________ 62 2.3.7 Power generation expansion possibilities in the Southern African region - summary 63 2.3.1. CO2 emission sources from power generation in the Southern African region – summary 64

2.4. Country details – Southern African region 65 2.4.1. South Africa ________________________________________________________ 65 2.4.2. Namibia ___________________________________________________________ 71 2.4.3. Mozambique _______________________________________________________ 77 2.4.4. Botswana __________________________________________________________ 82

CHAPTER 3 Storage capacity ____________________________________________________ 86

3.1.1. Identification method ________________________________________________ 86 3.1.2. results ____________________________________________________________ 86 3.1.3. storage capacity in the Balkan region ____________________________________ 88 3.1.4. Storage capacity in the Southern Africa region ____________________________ 91

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CHAPTER 4 Identification of cost elements ________________________________________ 97

4.1. Assessment of CCS capturing technologies and costs 97 4.1.1. Compilation of literature findings for different capturing technologies _________ 97 4.1.2. Adaptation of the cost elements to the local circumstances _________________ 100

4.2. Assessment of transport costs 101

4.3. Assessment of storage costs 102 4.3.1. Methodology _____________________________________________________ 102 4.3.2. Size of storage projects______________________________________________ 103 4.3.3. Cost curves _______________________________________________________ 105

CHAPTER 5 Techno-economic model and simulations results ________________________ 110

5.1. General model description 110

5.2. Options for modeling CCS in techno-economic optimization models 111 5.2.1. Technology data ___________________________________________________ 111 5.2.2. Basic approach: dedicated connections _________________________________ 112 5.2.3. Extended Approach: separation of capture, transport and storage ___________ 113 5.2.4. Potential Extensions to the modeling approaches _________________________ 117

5.3. General Scenario Description 117

5.4. Simulation assumptions – Balkan region 118

5.5. CO2 storage and transport in Balkan region 119

5.6. Candidate power plants in Balkan region 120

5.7. Screening curve analysis of thermal power candidates in Balkan region 121

5.8. Simulation results – Balkan region 123 5.8.1. Reference (least cost) scenario _______________________________________ 124 5.8.2. Efficiency Scenario _________________________________________________ 131 5.8.3. Base Line Scenario _________________________________________________ 133 5.8.4. Rnewable Electricity Sources (RES Policy) scenario ________________________ 136 5.8.5. CO2 Price Scenario _________________________________________________ 139 5.8.6. The CO2 Limited Scenario ____________________________________________ 153 5.8.7. CCS Target Scenario ________________________________________________ 171

5.9. Comparison of scenarios for Balkan region 174

5.10. Conclusions for Balkan region 182

5.11 scenario description – Southern African region 186

5.12 General modeling assumptions – Southern African region 186

5.13 CO2 capture, storages and transport in the Southern African region 187

5.14 Power generation options for the Southern African region 189

5.15 Screening curve analysis 190

5.16 Simulation results – Southern African region 194 5.16.1 Reference Scenario _________________________________________________ 194 5.16.2 Baseline scenario __________________________________________________ 196 5.16.3 Baseline scenario with EOR/ECBM benefits ______________________________ 200 5.16.4 Co2 Price scenario at - 25 USD/ton _____________________________________ 201

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5.16.5 Co2 Price scenario - 50 USD/ton _______________________________________ 204 5.16.6 Co2 Price scenario - 100 USD/ton ______________________________________ 208

5.17 scenario comparison 210

5.18 Comparison of scenarios for Southern African region 213

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LIST OF FIGURES

Figure 1: Comparison of total CO2 emission across scenarios for the Balkan region _____________ 6 Figure 2: Comparison of average generation costs across scenarios for the Balkan region _______ 7 Figure 3: Comparison of total CO2 emission across the scenarios for the Southern African region _ 8 Figure 4: Comparison of average generation costs including CO2 price across scenarios for the

Southern African Region _______________________________________________________ 8 Figure 5: Countries to be referred to as the Balkan Region _______________________________ 24 Figure 6: Structure of generation capacities in the Balkan region (2010) ____________________ 27 Figure 7: Electricity generation, consumption and exchange in Balkan region in 2009 _________ 29 Figure 8: Interconnection lines in South East Europe in 2008 _____________________________ 30 Figure 9: Estimated total electricity consumption in the Balkan region until 2030 _____________ 32 Figure 10: Power transmission system in Croatia ______________________________________ 40 Figure 11: Power transmission system in Bosnia and Herzegovina _________________________ 44 Figure 12: Power transmission system in Serbia _______________________________________ 46 Figure 13: Power transmission system in Kosovo ______________________________________ 50 Figure 14: Power transmission system in Montenegro __________________________________ 52 Figure 15: Power transmission system in Albania ______________________________________ 55 Figure 16: Power transmission system in Macedonia ___________________________________ 58 Figure 17: Southern African region _________________________________________________ 59 Figure 18: Structure of installed capacity for Southern African countries ____________________ 61 Figure 19: Power Transmission System for the SAPP ____________________________________ 62 Figure 20: Estimated electricity system demand in the Southern African region up to 2030 _____ 63 Figure 21: South African Power Network with interconnections to neighbouring countries _____ 70 Figure 22: Namibian Transmission System with future build plans _________________________ 76 Figure 23: Mozambiquan transmission network _______________________________________ 81 Figure 24: Botswana Transmission Network __________________________________________ 84 Figure 25: Main tectonic units of Alpine fold-and-thrust belt and Alpine-Carpathian-Dinaric

Mountains. The Pannonian Basin groups several subbasins. __________________________ 89 Figure 26: (Left) Existing and undiscovered hydrocarbon fields in the Pannonian Basin ________ 89 Figure 27: Overview of hydrocarbon fields off-shore in South Africa with indication of seismic

coverage and typical structure to be expected. The on-shore opportunities relate to coal __ 92 Figure 28: Location of off-shore petroleum basins (Zululand which continues to Mozambique

basins; Durban, Outeniqua, Orange which continues in Namibia basins) ________________ 93 Figure 29: Location of off-shore petroleum basins in Namibia (left) and Mozambique (right) ____ 94 Figure 30: The Karoo Supergroup in Southern Africa in the Main Karoo Basin of South Africa and the

Great Kalahari Basin ( labelled in yellow) covering Namibia, Botswana, Zimbabwe and South Africa _____________________________________________________________________ 94

Figure 31: CO2 pipeline diameter in function of the mass flow ___________________________ 101 Figure 32: Summary of CO2-storage life-cycle phases and milestones _____________________ 102 Figure 33: Size distribution of existing hydrocarbon fields and predicted undiscovered reserves for

the Balkan region __________________________________________________________ 104 Figure 34: Size distribution of existing hydrocarbon fields and predicted undiscovered reserves for

the Southern African region __________________________________________________ 104 Figure 35: Cost curve for storage in on-shore saline aquifers with price as a function of the size of a

project. Two different injection schemes are represented considering a CO2 injection flux of 2000 ton/day and 5000 ton/day respectively. ____________________________________ 105

Figure 36: Cost curve for storage in depleted hydrocarbon fields, with/without EOR/EGR. Note that no revenues from enhanced oil recovery are accounted for in the calculated cost. A

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conservative estimate of such revenues based on 8% recovery win and an oil price of 70 USD/bbl is indicated in green. _________________________________________________ 106

Figure 37: Cost curve for storage in an ECBM project as a function of total volume stored (i.e. according to the injectivity of the coal). Note: no revenues from enhanced CBM recovery are taken into account in this figure. ______________________________________________ 107

Figure 38: Cost curve for storage in leached out salt caverns. ____________________________ 108 Figure 39: Representation of an integrated CCS-electricity plant in the model _______________ 115 Figure 40: Representation of an integrated CCS-electricity plant in the model - a more Detailed

approach _________________________________________________________________ 116 Figure 41: Screening curve analysis for Balkan region (carbon price 0 USD/ton CO2) __________ 122 Figure 42: Screening curve analysis for Balkan region (carbon price 25 USD/ton CO2) _________ 122 Figure 43: Screening curve analysis for Balkan region (carbon price 50 USD/ton CO2) _________ 123 Figure 44: Screening curve analysis for Balkan region (carbon price 100 USD/ton CO2) ________ 123 Figure 45: Electricity generation for the Reference scenario for Balkan region _______________ 124 Figure 46: Installed generation power fo the Reference scenario for Balkan region ___________ 125 Figure 47: Marginal system price for the Reference scenario for Balkan region ______________ 126 Figure 48: CO2 emissions from electricity production for the Reference scenario for Balkan region

_________________________________________________________________________ 126 Figure 49: Carbon intensity of electricity production for the Reference scenario for Balkan region

_________________________________________________________________________ 127 Figure 50: Share of CCS based generation in the Reference EOR scenario for Balkan region ____ 128 Figure 51: CO2 stored in the Reference EOR scenario for Balkan region ____________________ 128 Figure 52: Electricity generation for the Reference EOR scenario for Balkan region ___________ 129 Figure 53: Installed generation power for the Reference EOR scenario for Balkan region ______ 129 Figure 54: Marginal system price for the Reference EOR scenario for Balkan region __________ 130 Figure 55: CO2 emissions from electricity production for the Reference EOR scenario for Balkan

region ___________________________________________________________________ 130 Figure 56: Electricity generation for the Efficiency scenario for Balkan region _______________ 132 Figure 57: Installed generation power for the Efficiency scenario for Balkan region___________ 132 Figure 58: Marginal system price for the Efficiency scenario for Balkan region ______________ 133 Figure 59: CO2 emissions from electricity production for the Efficiency scenario for Balkan region

_________________________________________________________________________ 133 Figure 60: Electricity generation for the Base Line scenario for Balkan region _______________ 134 Figure 61: Installed generation power for the Base Line scenario for Balkan region ___________ 135 Figure 62: Marginal system price for the Base Line scenario for Balkan region _______________ 135 Figure 63: CO2 emissions from electricity production for the Base Line scenario for Balkan region

_________________________________________________________________________ 136 Figure 64: Electricity generation for the RES scenario for Balkan region ____________________ 137 Figure 65: Installed generation power for the RES scenario for Balkan region _______________ 138 Figure 66: Marginal system price for the RES scenario for Balkan region ___________________ 138 Figure 67: CO2 emissions from electricity production for the RES scenario for Balkan region____ 139 Figure 68: Different levels of CO2 price used in the simulation ___________________________ 140 Figure 69: Electricity generation for the CO2 Price scenario – Case 1 for Balkan region ________ 142 Figure 70: Installed generation power for the CO2 Price scenario – Case 1 for Balkan region ____ 142 Figure 71: Marginal system price for the CO2 Price scenario – Case 1 for Balkan region ________ 143 Figure 72: CO2 emissions from electricity production for the CO2 Price scenario – Case 1 for Balkan

region ___________________________________________________________________ 143 Figure 73: Electricity generation for the CO2 Price scenario – Case 2 for Balkan region ________ 144 Figure 74: Installed generation power for the CO2 Price scenario – Case 2 for Balkan region ____ 145 Figure 75: Marginal system price for the CO2 Price scenario – Case 2 for Balkan region ________ 145

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Figure 76: CO2 emission from electricity production for the CO2 Price scenario – Case 2 for Balkan region ___________________________________________________________________ 146

Figure 77: CO2 stored in the CO2 Price scenario – Case 3 for Balkan region _________________ 147 Figure 78: Share of CCS based generation in the CO2 Price scenario – Case 3 for Balkan region _ 147 Figure 79: Electricity generation for the CO2 Price scenario – Case 3 for Balkan region ________ 148 Figure 80: Installed generation power for the CO2 Price scenario – Case 3 for Balkan region ___ 148 Figure 81: Marginal system price for the CO2 Price scenario – Case 3 for Balkan region _______ 149 Figure 82: CO2 emissions from electricity production for the CO2 Price scenario – Case 3 for Balkan

region ___________________________________________________________________ 149 Figure 83: Share of CCS based generation in the CO2 Price scenario – Case 3 for Balkan region _ 150 Figure 84: CO2 stored in the CO2 Price scenario – Case 4 for Balkan region _________________ 150 Figure 85: Electricity generation for the CO2 Price scenario – Case 4 for Balkan region ________ 151 Figure 86: Installed generation power for the CO2 Price scenario – Case 4 for Balkan region ___ 151 Figure 87: Marginal system price for the CO2 Price scenario – Case 4 for Balkan region _______ 152 Figure 88: CO2 emissions from electricity production for the CO2 Price scenario – Case 4 for Balkan

region ___________________________________________________________________ 152 Figure 89: Electricity generation for the CO2 Limited scenario - Case 1 for Balkan region ______ 154 Figure 90: Share of CCS based generation for the CO2 Limited scenario - Case 1 for Balkan region154 Figure 91: Installed generation power for the CO2 Limited scenario - Case 1 for Balkan region __ 155 Figure 92: Marginal system price for the CO2 Limited scenario - Case 1 for Balkan region ______ 155 Figure 93: CO2 emissions from electricity production for the CO2 Limited scenario - Case 1 for

Balkan region _____________________________________________________________ 156 Figure 94: Electricity generation for the CO2 Limited scenario - Case 2 for Balkan region ______ 157 Figure 95: Share of CCS based generation for the CO2 Limited scenario - Case 2 for Balkan region157 Figure 96: Installed generation power for the CO2 Limited scenario - Case 2 for Balkan region __ 158 Figure 97: Marginal system price for the CO2 Limited scenario - Case 2 for Balkan region ______ 158 Figure 98: CO2 emissions from electricity production for the CO2 Limited scenario - Case 2 for

Balkan region _____________________________________________________________ 159 Figure 99: Electricity generation for the CO2 Limited scenario - Case 3 for Balkan region ______ 160 Figure 100: Share of CCS based generation for the CO2 Limited scenario - Case 3 for Balkan region

________________________________________________________________________ 160 Figure 101: Installed generation power for the CO2 Limited scenario - Case 3 for Balkan region _ 161 Figure 102: Marginal system price for the CO2 Limited scenario - Case 3 for Balkan region _____ 161 Figure 103: CO2 emissions from electricity production for the CO2 Limited scenario - Case 3 for

Balkan region _____________________________________________________________ 162 Figure 104: Electricity generation for the CO2 Limited scenario - Case 4 for Balkan region _____ 163 Figure 105: Share of CCS based generation for the CO2 Limited scenario - Case 4 for Balkan region


Balkan region _____________________________________________________________ 165 Figure 109: Electricity generation for the CO2 Limited scenario - Case 5 for Balkan region _____ 166 Figure 110: Share of CCS based generation for the CO2 Limited scenario - Case 5 for Balkan region


Balkan region _____________________________________________________________ 168 Figure 114: Electricity generation for the CO2 Limited scenario - Case 6 for Balkan region _____ 169

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Figure 115: Share of CCS based generation for the CO2 Limited scenario - Case 6 for Balkan region _________________________________________________________________________ 169

Figure 116: Installed generation power for the CO2 Limited scenario - Case 6 for Balkan region _ 170 Figure 117: Marginal system price for the CO2 Limited scenario - Case 6 for Balkan region _____ 170 Figure 118: CO2 emissions from electricity production for the CO2 Limited scenario - Case 6 for

Balkan region ______________________________________________________________ 171 Figure 119: Share of CCS based generation in the CCS Target scenario for Balkan region ______ 172 Figure 120: CO2 stored in the CCS Target scenario for Balkan region_______________________ 172 Figure 121: Electricity generation for the CCS Target scenario for Balkan region _____________ 173 Figure 122: Installed generation power for the CCS Target scenario for Balkan region_________ 173 Figure 123: Marginal system price for the CCS Target scenario for Balkan region_____________ 174 Figure 124: CO2 emission from electricity production for the CCS Target scenario for Balkan region

_________________________________________________________________________ 174 Figure 125: Comparison of total discounted costs across scenarios for Balkan region _________ 177 Figure 126: Comparison of the marginal system price across scenarios for Balkan region ______ 178 Figure 127: Comparison of average generation costs across scenarios for Balkan region _______ 179 Figure 128: Comparison of total CO2 emissions across scenarios for Balkan region ___________ 180 Figure 129: Cumulative CO2 emissions savings across scenarios for Balkan region ____________ 181 Figure 130: Investment cost evolution due to technology learning ________________________ 190 Figure 131: Screening curves for the Southern African region - no CO2 Price ________________ 191 Figure 132: Screening curves for the Southern African region - CO2 Price of 25 USD/ton _______ 192 Figure 133: Screening curves for the Southern African region - CO2 Price of 50 USD/ton _______ 192 Figure 134: Screening curves for Southern African region - CO2 Price of 100 USD/ton _________ 193 Figure 135: Electricity generation for Southern African region – Reference Scenario __________ 194 Figure 136 New Investment in Power Generation for Southern African region – Reference scenario

_________________________________________________________________________ 195 Figure 137 CO2 emissions and average generation costs for Southern African region – Reference

scenario __________________________________________________________________ 196 Figure 138: Electricity generation for Southern African region – Baseline scenario ___________ 198 Figure 139: New investment in power generation for Southern African Region – Baseline scenario

_________________________________________________________________________ 199 Figure 140: CO2 emissions and average generation costs for Southern African region – Baseline

scenario __________________________________________________________________ 200 Figure 141 Cumulative CO2 storage costs for Southern African region – Baseline scenario _____ 200 Figure 142: Cumulative CO2 storage costs for Southern African region – Baseline with EOR/ECBM

scenario __________________________________________________________________ 201 Figure 143: Electricity generation for Southern African region –25 USD/ton CO2 Price scenario _ 202 Figure 144: New investment in power generation for Southern African region – 25 USD/ton CO2

Price scenario _____________________________________________________________ 203 Figure 145: CO2 emissions and average generation costs for Southern African region – 25 USD/ton

CO2 scenario ______________________________________________________________ 204 Figure 146: Cumulative CO2 storage costs for Southern African region – 25 USD/ton CO2 scenario

_________________________________________________________________________ 204 Figure 147: Electricity Generation for Southern African region – 50 USD/ton CO2 Price scenario 205 Figure 148: New investment in power generation for Southern African region –50 USD/ton CO2

Price scenario _____________________________________________________________ 205 Figure 149: CO2 emissions and average generation costs for Southern African region –50 USD/ton

CO2 scenario ______________________________________________________________ 207 Figure 150: Cumulative CO2 storage costs for Southern African region –50 USD/ton CO2 scenario 207 Figure 151: Electricity generation for Southern African region – 100 USD/ton CO2 Price scenario 208

List of Figures

16

Figure 152: New investment in power generation for Southern African region – 100 USD/ton CO2 Price scenario _____________________________________________________________ 209

Figure 153: CO2 emissions and average generation costs for Southern African region – 100 USD/ton CO2 scenario ______________________________________________________________ 209

Figure 154: Cumulative CO2 storage costs for Southern African region – 100 USD/ton CO2 scenario ________________________________________________________________________ 210

Figure 155: Comparison of average generation costs excluding CO2 costs across scenarios for Southern African region _____________________________________________________ 212

Figure 156: Comparison of average generation costs Including CO2 costs across scenarios for Southern African region _____________________________________________________ 212

Figure 157: Comparison of annual CO2 emissions across scenarios for Southern African region _ 213

List of Tables

17

LIST OF TABLES

The following table summarizes the main development indicators for the jurisdictions in the Balkan region. Table 1: Key indicators for jurisdictions in Balkan region in 2008 (Source: IEA and EIHP) __________________________________________________________________________ 26

Table 2: Available generation capacity in the Balkan region (2010) _________________________ 27 Table 3: Electricity generation and consumption in Balkan region in 2009 ___________________ 28 Table 4: On-going and planned projects for interconnection in Balkan region ________________ 31 Table 5: Estimated total electricity demand in the Balkan region up to 2030 _________________ 31 Table 6: Indicative hydro potential in the Balkan region _________________________________ 33 Table 7: Electricity production capacities and operational conditions in a reference year(2010) __ 35 Table 8: Key indicators for Croatia in 2008 ____________________________________________ 38 Table 9: Electricity generation capacity in Croatia (HEP Group ownership) ___________________ 39 Table 10: Key indicators for Bosnia and Herzegovina in 2008 _____________________________ 41 Table 11: Existing power plants in Bosnia and Herzegovina _______________________________ 42 Table 12: Potential for development of power generation in Bosnia and Herzegovina _________ 43 Table 13: Key indicators for Serbia in 2008 ____________________________________________ 45 Table 14: Key indicators for Kosovo in 2008 (2005) _____________________________________ 48 Table 15: Installed capacities in the Kosovo power system _______________________________ 49 Table 16: Key indicators for Montenegro in 2008 (2005) _________________________________ 51 Table 17: Key indicators for Albania in 2008___________________________________________ 53 Table 18: Installed hydro power capacities in Albania ___________________________________ 53 Table 19: Interconnection lines between Albania and neighboring power systems ____________ 55 Table 20: Key indicators for Macedonia in 2008 ________________________________________ 56 Table 21: Installed capacity in thermal power plants in Macedonia ________________________ 56 Table 22: Installed capacity in hydro power plants in Macedonia __________________________ 57 Table 23: SAPP Membership _______________________________________________________ 59 Table 24: Key indicators for the Southern African region in 2008 __________________________ 60 Table 25: Available generation capacity in the region ___________________________________ 60 Table 26: Summary of electricity consumption, production and exchange in Southern Africa ____ 61 Table 27: Electricity consumption forecasts by country in the Southern African region _________ 62 Table 28: Hydro options in the Southern African region _________________________________ 64 Table 29: South Africa coal plant CO2 emissions for 2006 ________________________________ 64 Table 30: Power sector CO2 emissions for Botswana, Mozambique and Namibia ______________ 65 Table 31: Key indicators for South Africa in 2008 (Source: IEA) ____________________________ 66 Table 32: Input parameters for existing coal plants in South Africa _________________________ 67 Table 33: Input parameters for existing plants other than coal in South Africa ________________ 68 Table 34: Committed build plan from DOE IRP2010 _____________________________________ 69 Table 35: Major transmission assets expected to be installed _____________________________ 70 Table 36: Key Indicators for Namibia in 2000 __________________________________________ 71 Table 37: Parameters for installed generation capacity of thermal power plants in Namibia _____ 73 Table 38: Parameters for installed generation capacity of thermal power plants in Namibia _____ 73 Table 39: Electricity generated, imported and exported in Namibia June2008-June2009 _______ 74 Table 40: Key Indicators for Mozambique ____________________________________________ 77 Table 41: Parameters for installed generation capacity of thermal power plants in Mozambique _ 79 Table 42: Parameters for installed generation capacity of hydro power plants in Mozambique __ 79 Table 43: Key Indicators for Botswana _______________________________________________ 82 Table 44: Parameters for installed generation capacity of thermal power plants in Botswana ___ 83 Table 45: Technical and economical characteristics of reference power plants and CCS integrated

power plants (see footnote 68) ________________________________________________ 99

List of Tables

18

Table 46: Exchange rates (2005 LCU/$) and Purchasing Power Parities for GDP, Machinery and Equipment and construction costs in South African and Balkan region ________________ 101

Table 47: Assumptions made and approach followed to calculate cost curves per type of storage. ________________________________________________________________________ 109

Table 48: Fuel prices used in simulation for Balkan region ______________________________ 119 Table 49: Data on CO2 storage volume, storage and transportation costs used in simulation for

Balkan region _____________________________________________________________ 120 Table 50: Power expansion candidates in Balkan region ________________________________ 121 Table 51: Electricity generation for the Reference scenario for Balkan region _______________ 124 Table 52: Installed generation power for the Reference scenario for Balkan region __________ 125 Table 53: CO2 emissions from electricity production for the Reference scenario for Balkan region

________________________________________________________________________ 127 Table 54: Electricity generation for the Reference EOR scenario for Balkan region ___________ 129 Table 55: Installed generation power for the Reference EOR scenario for Balkan region ______ 129 Table 56: CO2 emissions from electricity production for the Reference EOR scenario for Balkan

region ___________________________________________________________________ 130 Table 57: Final electricity demand in the Balkan region until 2030 for the Efficiency Scenario __ 131 Table 58: Electricity generation for the Efficiency scenario for Balkan region _______________ 132 Table 59: Installed generation power for the Efficiency scenario for Balkan region ___________ 132 Table 60: CO2 emissions from electricity production for the Efficiency scenario for Balkan region 133 Table 61: Electricity generation for the Base Line scenario for Balkan region ________________ 134 Table 62: Installed generation power for the Base Line scenario for Balkan region ___________ 135 Table 63: CO2 emissions from electricity production for the Base Line scenario for Balkan region 136 Table 64: Forced construction of renewables in the RES scenario for Balkan region __________ 136 Table 65: Electricity generation for theRES scenario for Balkan region _____________________ 137 Table 66: Installed generation power for the RES scenario for Balkan region ________________ 137 Table 67: CO2 emissions from electricity production for the RES scenario for Balkan region ____ 139 Table 68: Description of different cases simulated under the CO2 Price scenario for Balkan region

________________________________________________________________________ 140 Table 69: Electricity generation for the CO2 Price scenario – Case 1 for Balkan region_________ 141 Table 70: Installed generation power for the CO2 Price scenario – Case 1 for Balkan region ____ 142 Table 71: CO2 emission from electricity production for the CO2 Price scenario – Case 1 for Balkan

region ___________________________________________________________________ 143 Table 72: Electricity generation for the CO2 Price scenario – Case 2 for Balkan region_________ 144 Table 73: Installed generation power for the CO2 Price scenario – Case 2 for Balkan region ____ 144 Table 74: CO2 emissions from electricity production for the CO2 Price scenario – Case 2 for Balkan

region ___________________________________________________________________ 146 Table 75: Electricity generation for the CO2 Price scenario – Case 3 for Balkan region_________ 147 Table 76: Installed generation power for the CO2 Price scenario – Case 3 for Balkan region ____ 148 Table 77: CO2 emissions from electricity production for the CO2 Price scenario – Case 3 for Balkan

region ___________________________________________________________________ 149 Table 78: Electricity generation for the CO2 Price scenario – Case 4 for Balkan region_________ 151 Table 79: Installed generation power for the CO2 Price scenario – Case 4 for Balkan region ____ 151 Table 80: CO2 emission from electricity production for the CO2 Price scenario – Case 4 for Balkan

region ___________________________________________________________________ 152 Table 81: Description of different cases simulated under the CO2 Limited scenario for Balkan region

________________________________________________________________________ 153 Table 82: Electricity generation for scenario CO2 Limited - Case 1 for Balkan region __________ 154 Table 83: Installed generation power for the CO2 Limited scenario - Case 1 for Balkan region __ 155 Table 84: CO2 emissions from electricity production for the CO2 Limited scenario - Case 1 for Balkan

region ___________________________________________________________________ 156

List of Tables

19

Table 85: Electricity generation for the CO2 Limited scenario - Case 2 for Balkan region _______ 157 Table 86: Installed generation power for the CO2 Limited scenario - Case 2 for Balkan region ___ 158 Table 87: CO2 emissions from electricity production for the CO2 Limited scenario - Case 2 for Balkan

region ___________________________________________________________________ 159 Table 88: Electricity generation for the CO2 Limited scenario - Case 3 for Balkan region _______ 160 Table 89: Installed generation power for the CO2 Limited scenario - Case 3 for Balkan region ___ 161 Table 90: CO2 emissions from electricity production for the CO2 Limited scenario - Case 3 for Balkan




region ___________________________________________________________________ 171 Table 100: Electricity generation for the CCS Target scenario for Balkan region ______________ 173 Table 101: Installed generation power for the CCS Target scenario for Balkan region _________ 173 Table 102: CO2 emission from electricity production for the CCS Target scenario for Balkan region

_________________________________________________________________________ 174 Table 103: Comparison of results across scenarios for Balkan region – Part I ________________ 175 Table 104: Comparison of results across scenarios for Balkan region – Part II _______________ 176 Table 105: Comparison of results across scenarios for Balkan region – Part III _______________ 176 Table 106: Fuel price assumptions for Southern African region ___________________________ 187 Table 107: Capture technologies, options and parameters for the Southern African region ____ 187 Table 108: CO2 Storage Options, Volumes and Costs for Southern Africa ___________________ 188 Table 109: CO2 transport options for the Southern African region ________________________ 189 Table 110: Generic options available in the region and associated model input parameters ____ 190 Table 111: Share of Electricity Generation for Southern African region – Reference scenario ___ 195 Table 112 Total capacity for Southern African region – Reference scenario _________________ 195 Table 113: DOE 2011 IRP “Revised balance” expansion plan _____________________________ 197 Table 114: Share of generation for Southern African region – Baseline scenario _____________ 198 Table 115: Total Capacity for Southern African region – Baseline scenario __________________ 199 Table 116: Share of generation for Southern African region – 25 USD/ton CO2 scenario _______ 202 Table 117: Total capacity for Southern African region – 25 USD/ton CO2 scenario ____________ 203 Table 118: Share of generation for Southern African region –50 USD/ton CO2 scenario________ 205 Table 119: Total capacity for Southern African region –50 USD/ton CO2 scenario ____________ 206 Table 120: Share of generation for Southern African region – 100 USD/ton CO2 scenario ______ 208 Table 121: Total capacity for Southern African region – 100 USD/ton CO2 scenario ___________ 209 Table 122: Comparison of results across scenarios for Southern African region ______________ 211 Table 123: Share of generation summary by fuel/technology group for Southern African region 211 Table 124: Summary table storage optios in the Balkan region ___________________________ 219 table 125: Summary table storage options Southern African region _______________________ 229

List of Acronyms

20

LIST OF ACRONYMS

bbl CBM CCS ECBM EGR EOR

Barrel(s) Coal-bed methane (recovery) Carbon Capture and Storage Enhanced coal-bed methane (recovery) Enhanced gas recovery Enhanced oil recovery

GHG GIP HPP MMBO n.d. OOIP

Greenhouse gases Gas in place Hydro Power plant Millions of metric barrels of oil Not determined / no data Oil originally in place

SCPC Supercritical Powder Coal (plant) NGCC Natural gas combined cycle power plants IGCC Integrated gasification combined cycle power pants HPP Hydro power plants TPP Thermal power plants NPP Nuclear power plants PPP Purchasing Power Parity

CHAPTER 1 Methodology and Structure

21

CHAPTER 1 METHODOLOGY AND STRUCTURE

1.1. INTRODUCTION

Carbon capturing and storage (CCS) is a promising technology for reducing CO2 emissions in the power sector in the over the coming decades. CCS involves capturing of CO2 from the flue gasses in thermal power plants, transport of CO2 via pipelines or other means (ship, train, truck) and injection of the CO2 in a suitable storage site. This study assesses the potential deployment of CCS in the Balkan region and in the South African region for the period up to 2030. There are different aspects that could be considered in this evaluation: legal and regulatory aspects, technological aspects, economic conditions, technical limitations, and interaction with environmental and climate policies, among others. This study focuses on the interaction between the economic and the technological conditions. The objective of this study does not encompass a detailed technical examination of the chemical processes required for CCS, and so the literature has been screened to find the relevant parameters for different CCS technologies, including the cost of the technologies and the loss of efficiency in net electricity output. An evaluation of the technical potential of CCS involves the following aspects: making an inventory of the CO2 sources and how these would evolve in the coming 20 years (defining the maximum capturing capacity), investigating whether transport of CO2 involves any capacity constraints (defining maximum transport capacity), making an inventory of possible storage options (defining the maximum storage capacity for each) and the technical potential is quantified by taking account of the maximum capaturing capacity, the maximum transport capacity and the maximum storage capacity. It is clear that disregarding the economic conditions would result in unrealistically high potential estimates. A techno-economic assessment additionally considers economic constraints (in terms of available budget) from a government point of view or analyzes the economic drivers (what are the incentives to invest in CCS) from a market point of view. In this study we take the second approach, i.e. we look at the potential deployment of CCS from a market point of view. For this, we have used the techno-economic model MESSAGE. The motivation behind this approach is described in the next section. The layout of the report is the following: Chapters 2, 3 and 4 define the input parameters for the MESSAGE model. In chapter 2 the regional and country profiles from a technical potential standpoint for CO2 capture are presented as well as the current stuation of electricity generation. This relates to the technologies used for the production of electricity, the transmission network and the policy actions that will have an influence on the evolution of electricity production. A scenario for the evolution of electricity consumption is also presented. Chapter 3 is devoted to the storage potential in the two regions and chapter 4 defines the economic parameters related to capturing and storage. Chapter 5 gives the results and the conclusions for the two regions.

1.2. METHODOLOGY OF TECHNO-ECONOMIC OPTIMIZATION MODELS

The production of electricity, as represented in techno-economic optimization models, is conditioned by economic laws and Ohm’s law. The economic laws require that no more resources are used than are strictly required, or, expressed in a more familiar way, that electricity is as cheap as possible. This is

CHAPTER 1 Methodology and structure

22

valid, whether produced in a free market or in a government regulated market. Ohm’s law states that electricity is produced for immediate consumption, i.e. the production must follow consumption immediately. Fluctuations in demand cause stopping and start-up of existing production facilities and increasing demand requires an expansion of the production facilities. Exploring the potential of CCS deployment requires that the model sufficiently represent the typical characteristics of the electricity sector, i.e. the technical and economical characteristics of the different technologies in the electricity sector, the prices of fuels, and the fluctuations in demand. Techno-economic optimisation models have been developed to deal with the specificities of the electricity sector. Technical optimisation models have a long history, going back to the early eighties. They have very attractive properties for exploring the potential development of CCS in the electricity sector, since they represent the electricity sector with enough resolution to explore CCS deployment against various alternatives, such as renewable energies and traditional fossil fuel electricity production technologies. Therefore it was decided that optimisation models are the most appropriate tool for this type of analysis. The driving factor (or the decision making mechanism) in these models is the total discounted system cost. The system cost is the total cost for the supply of electricity to end users (households and business) in a finite horizon (for instance the period 2010-2030). All types of costs, such as investment costs, fuel costs and operating costs, are considered in a consistent manner, and future costs are discounted by the discount rate. Unless forced by the model user, the methodology does not require any arbitrary fixing of a trajectory for CCS or any other energy technology. The model defines both new installations and dispatching of new and existing installations within certain boundaries that are defined by the model user. The model solution simulates the perfect market under the assumption of perfect foresight. From an economic point of view the solution is optimal. The choice of the discount factor is an important issue, as it determines the balancing between capital costs (mainly investment) and operating cost (mainly fuel). Any technology has a capital cost to be paid during the construction phase, and a variable operating cost (mainly fuel cost) to be paid during the operational lifetime. As the operational lifetime extends over a long period, discounting has more effect on the variable costs, and the higher the discount rate, the less weight is given to the variable cost in the objective function. The choice of the discount rate determines how the results should be interpreted. When a social discount rate is applied (3%-4%), then the model solution is optimal from a social welfare point of view, ensuring a significant amount of intergenerational equity, without risk aversion. However, when a higher discount rate is used, then the model simulates the behaviour of a private investor with some risk aversion. A discussion on quantifying the social discount rate is beyond the scope of this report, but a suggested resource to learn more about the debate can be found in

Moore et al. 2004.2 In this study, a discount rate of 8 % has been adopted. As the model is expressed in constant prices (excluding inflation) this value might represent the expected return on ivestment from a private investor. Techno-economical optimization models can initially seem very complex, mainly by the relatively exhaustive way of representing the sector specificities, but in fact they are based on simple transparent and sound economic principles. TIMES, MARKAL and MESSAGE are commercially available software tools that are suitable for this kind of analysis. They are based on the same economic principles, have a similar flexibility in representing different technologies, and all would have provided sufficient results for this excercise. CCS is not a standard option in any of these packages however, and specific model additions would have been necessary for all three of the modelling tools. This is discussed further in chapter 5.

2 Moore, M. ,Boordman,A., Weimer,L., Greenberg,H., (2004).”Just Give Me a Number!” Practical values for

the Social Discount Rate. Journal of Policy analysis and Management V23 n4 p789-812


23

The choice for the MESSAGE model for this study has been based on the following practical considerations:

Existing MESSAGE models for the electricity sector are available for all of the countries considered.

MESSAGE software if free of charge, allowing transfer of the model without additional costs.


24

CHAPTER 2 REGIONAL OVERVIEWS

2.1. BALKAN REGION

In this chapter the main existing emission sources in power system of Balkan region were identified. For the purposes of the report, the Balkan region comprises the following jurisdictions: Croatia (HR), Bosnia and Herzegovina (BA), Serbia (RS), Kosovo (KO), Montenegro (MN), Albania (AL) and Former Yugoslavian Republic of Macedonia (MK).

Figure 5: Countries to be referred to as the Balkan Region

A short introduction on regional initiatives for harmonization of energy markets (Energy Community) is followed by the main development indicators for the jurisdictions under consideration, summaries of the power systems (production capacities, generation, exchange and consumption), and an overview of regional transmission networks and CO2 emitting sources from the power sector. It is important to understand where the CO2 sources are in the region, as these make up the potential sites for CCS technology deployment. Further detail on each of the countries examined individually is also provided.

2.1.1. ENERGY COMMUNITY

The important framework in which power and energy systems operate throughout the Balkan area is the the European Union (EU) and the ongoing and expected integration processes of the countries into the European energy map. The conflicts of the 1990s led to the disintegration of a unified energy system. The South East European region needed a framework in which it could cooperate on:

1. Rebuilding energy networks,


25

2. Ensuring the stability vital for investment, and 3. Creating the conditions in which its economies can be rebuilt effectively.

Parallel to the evolution of the European internal energy market, the EU took an active role in promoting stability and sustainable development in South East Europe. The EU, subsequently, put forward a proposal outlining the principles and the institutional necessities on which the development of the regional electricity market for the South East European (SEE) area should be based. The proposal ultimately would ensure the integration of the region into the European Union’s internal electricity market (the integration of the electricity market was the first initiative, later followed by the integration of gas markets and the harmonization of the whole legal framework for energy and environment). In October 2005 the European Community and Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Montenegro, the Former Yugoslav Republic of Macedonia, Romania, Serbia and UNMIK on behalf of Kosovo signed the Treaty establishing the Energy Community3. The Energy Community extends the EU internal energy market to South East Europe and beyond on the ground of a legally binding framework. The Parties to the Treaty are the EU on the one hand, and the Contracting Parties on the other, namely, Albania, Bosnia and Herzegovina, Croatia, former Yugoslav Republic of Macedonia, Montenegro, Serbia and Kosovo.4 The Treaty requires the Contracting Parties to implement important parts of the acquis communautaire, 5 which provides for the creation of a single energy market and the mechanism for the operation of network markets. It also establishes the institutions of the Energy Community, as well as the decision making process. Following the ratification and notification process, the Treaty entered into force on 1 July 2006. The Contracting Parties have committed themselves to implement the relevant acquis communautaire, to develop an adequate regulatory framework and to liberalize their energy markets in line with the acquis under the Treaty. The Treaty includes key EU legal acts in the area of electricity, gas, environment and renewable energy. The Treaty envisages that the main principles of EU competition policy are also applicable. In addition and following the established procedures, the Contracting Parties took up the commitment to implement a set of security of supply and energy efficiency related legislation. The acquis must be implemented within a fixed time frame and is supported by concrete Action Plans. A common regional approach concerning oil, renewable energy and the social dimensions of the energy reforms is also being developed. A strong institutional setting supports the process. This comprises a Ministerial Council, Permanent High Level Group, Regulatory Board, four Fora6 and a Secretariat. With its seat in Vienna, the Secretariat is the only permanently acting institution. It has currently a staff of 20 members, representing 11 nationalities, and monitors and assists the implementation process. Further to the

3 Treaty Establishing the Energy Community, 2005; Before the Treaty two Memorandums were created: Memorandum of Understanding on the Regional Energy Market in South East Europe and its Integration

into the European Community Internal Energy Market – The Athens Memorandum – 2003, 8 December 2003.

Memorandum of Understanding on the Regional Electricity Market in South East Europe and its Integration into the European Union Internal Electricity Market ("The Athens Memorandum – 2002"), 25 November 2002.

4 Whilst Moldova became a full member as of 1 May 2010, Ukraine officially acceded the Energy Community

on 1 Feb 2011. Georgia, Norway and Turkey take part as Observers. As of Feb 2011, 14 European Union Member States have the status of Participants. 5 Legal EU framework.

6 Forum is a regular annual meeting of contracting parties with advisory roles to the Energy Community.

There are Fora on Electricity, Gas, Oil and Social issues.


26

energy policy activities, it provides administrative support to the other Energy Community institutions and organizes annually some 40 events. In the Balkan area the electricity market is characterized by the domination of national power companies. In most cases these companies are publicly owned and control generation and distribution/supply assets. Only in Croatia is the transmission system operator (TSO) part of the national power company (vertically integrated). In other jurisdictions TSOs are separate companies from the generation/supply/distribution business. There is no organized market place and trade among parties is bilateral. In Montenegro, the power company was partially privatized by an Italian investor. In Albania and Macedonia the electricity distribution/supply businesses were privatized by Czech and Austrian investors, while in Kosovo the privatization of the distribution/supply branch is currently underway. Throughout the region there are private investors in the power generation area, mainly in the wind and other small-scale renewables, but there is also a substantial interest in large scale coal and hydro based projects. Apart from the existing and planned power generation projects in the Balkan region, future development of electricity markets is influenced by energy projects in neighboring systems, such as nuclear power programs in Romania, Bulgaria and Slovenia, foreseen connections to the Italian market, availability of natural gas, future obligations regarding reduction and/or stabilization of GHG emissions and obligations regarding the share of renewables and energy efficiency policies). It is expected that all countries will become full member countries of the EU by the end of the planning horizon explored in this study (i.e. by 2030).

2.1.2. MAIN DEVELOPMENT INDICATORS

The following table summarizes the main development indicators for the jurisdictions in the Balkan region. Table 1: Key indicators for jurisdictions in Balkan region in 2008 (Source: IEA and EIHP)

Indicator Croatia Bosnia and

Herzegovina Serbia Montenegro Kosovo Albania Macedonia Total

Population Million

4.43 3.77 7.35 0.62 2.0 3.14 2.04 23.35

GDP (PPP) billion USD 2000

67.12 34.31 51.08 4.90*** 5.60*** 5.66 15.08 183.75

Electricity consumption TWh

17.20 9.31 31.49 3.86 3.98 4.31 7.60 77.75

CO2 emission* million tons/yr

5.5 9.0 26.0 1.4 6.0 0.1 5.5 53.5

UNFCCC Annex I Non-Annex I Non-Annex I Non-Annex I not party Non-Annex I Non-Annex I -

Kyoto

-5% in 2008-2012

compared to 1990

level

ratified no

reduction

ratified no

reduction

ratified no reduction

not party ratified

no reduction


-

EU accession status and

expectation**

Candidate 2013

SAA (2011) 2020

SAA (2011) 2018

Candidate 2016

process pending

Potential candidate

2018

Candidate 2015

-

* From power sector only, estimated. ** SAA (Stabilization and Association Agreement); year in brackets next to SAA indicates expected entry into force of the SAA; year below is expected date for joining EU. *** Data reported in USD2008.

Source: IEA and EIHP


27

2.1.3. INSTALLED GENERATION CAPACITY IN BALKAN REGION – SUMMARY

The following table and figure summarize the installed generation capacities in the Balkan region. The data presented correspond to the end of 2010.

Table 2: Available generation capacity in the Balkan region (2010)

Jurisdiction HPP TPP NPP Other Total

Peak Load

System Reserve

MW %

Albania 1463 100 0 0 1563 1472 6

Kosovo 43 855 0 0 898 967 -7

Macedonia 503 907 0 0 1410 1512 -7

Montenegro 658 210 0 0 868 770 13

Croatia* 2119 1669 350* 102 4240 3120 36

Bosnia and Herzegovina

2064 1957 0 0 4021 2033 98

Serbia** 2835 4289 0 0 7124 6383 12

Total 9685 9987 350 102 20123 16257 24

* - NPP Krsko situated in Slovenia; 50% capacity credited to Croatia ** - without Kosovo units

Source: EIHP

In the Balkan region the total available generation capacity is approximately 20.1 GW. About half of the capacity is from thermal power plants (49.6%) and half from hydro and other, which are mainly small scale plants (wind, solar, biomass, landfill gas). The NPP credited to Croatia is located in Slovenia, and the Croatian national power company receives 50% of the power and energy based on the ownership structure.

Figure 6: Structure of generation capacities in the Balkan region (2010)

Source: EIHP

Peak load in the region is 16.2 GW. Region-wide system reserve amounts to 24%, which is low given the significant share of hydro and its potential unrelibability due its reliance on rainfall. The supply situation in some jurisdictions is critical, as local peak load is higher then total installed capacity (e.g. Kosovo, Macedonia), while some other systems face very low system reserve (e.g.

0%

20%

40%

60%

80%

100%

Alb

an

ia

Ko

so

vo

Ma

ce

do

nia

Mo

nte

ne

gro

Cro

ati

a*

BIH

Se

rbia

**

Other

NPP

TPP

HPP


28

Albania, Montenegro, Serbia). Only Bosnia and Herzegovina has enough reserve reserve capacity (almost double compared to the peak load). Thermal power plants in the region use mainly coal (domestic lignite/brown or imported hard coal). Gas/oil thermal power plants are well developed only in Croatia, while in other systems there are only one or two units resulting in minor shares in the total installed capacity.

2.1.4. ELECTRICITY CONSUMPTION, PRODUCTION AND EXCHANGE IN BALKAN REGION – SUMMARY

As in the rest of the world and Europe, the global economic crisis has influenced electricity consumption in Balkan region. Electricity consumption and wholesale electricity prices have decreased. However some systems have seen an increase of electricity consumption in the last few years (e.g. Kosovo and Albania). This is explained by the fact that these systems regularly apply load shedding, and that in the past it was difficult to supply electricity from abroad due to the local transmission network congestion and high prices. During 2006 and 2007, Albania experienced severe droughts which led to additional power cuts. Revitalization of some units (e.g. in Kosovo), and the end of the droughts has led to an increased availability and reliability of power generation in the last few years. Electricity generation, consumption and export-import balance in the Balkan region for 2009 are presented in the table and figure below.

Table 3: Electricity generation and consumption in Balkan region in 2009

Jurisdiction HPP TPP NPP Other

Total generation

Import-Export Total

consumption*

GWh

Albania 5125 48 0 0 5173 1411 6583

Kosovo 121 4675 0 0 4796 479 5275

Macedonia 1243 5009 0 0 6252 1544 7796

Montenegro 2062 617 0 0 2679 1078 3757

Croatia 6775 5190 2729 59 14753 2957 17710

Bosnia and Herzegovina 5954 8037 0 0 13991 -2990 11001

Serbia 11093 25019 0 0 36112 1366 37478

Total 32373 48595 2729 59 83756 5845 89601

Source: ENTSO-E and EIHP

Of these countries, the largest system is Serbia (approximately 42% of total regional consumption), followed by Croatia (20%) and Bosnia and Herzegovina (12%). Individual shares of other systems are below 10%. The region as a whole is a net importer of electricity. In 2009 about 6.5% of total electricity consumption was from imports. Electricity production in the region during 2009 was dominated by thermal power plants (mainly coal) which represented 58% of the total local electricity generation. The share of hydro generation was approximately 39%. The average capacity factor of thermal power plants was 55.5%. In absolute terms the largest importer of electricity is Croatia (approximately 3 TWh or 17% of total domestic consumption). In relative terms, large electricity importers are Montenegro (importing around 29% of domestic needs), Albania (21%) and Macedonia (20%). Bosnia and Herzegovina is the only net exporter in the region. In 2009 it exported approximately 3 TWh, or 30% above its domestic needs.


29

Figure 7: Electricity generation, consumption and exchange in Balkan region in 2009

Source: EIHP

2.1.5. POWER TRANSMISSION NETWORK IN BALKAN REGION – SUMMARY

Transmission systems in SEE today are relatively well developed. Compared to the other regions in Europe, SEE is characterized by a large number of interconnections (58) of 220 kV voltage level and above, as given in the following figure. One of the reasons for this robust system is that many interconnection lines were initially built as internal lines. For example, during the 1990’s, after the separation of the former federal republics that made up Yugoslavia into independent states, some former internal lines became interconnection lines. E.g. between Croatia and Bosnia and Herzegovina there are 20 interconnection lines today (400, 220 and 110 kV) with a total installed capacity of 5500 MVA (mega-volt-amper). This is more than the sum of the both countries’ peak loads.

-5

0

5

10

15

20

25

30

35

40

Albania Kosovo Macedonia Montenegro Croatia BIH Serbia

TW

h

Export-Import

Other

NPP

TPP

HPP

Total consumption*


30

Figure 8: Interconnection lines in South East Europe in 2008

IT

SK

HU

SI

HR

GRTR

BG

RO

MD

UKR

ALMK

ME

RS

ATARAD

ISALNITA

PORTILE de

FIERISACCEA

PIVDENO-

UKRAINSKA

VULKANESTI

SANDORFALVA

TANTARENI

KOZLODUY VARNA

DOBRUJA

MARITSA

ISTOK

BABAESKI

HAMITABAT

BLAGOEVGRAD

SOFIA

SKOPJE

DUBROVO

THESSALONIKIKARDIA

ARACHTOS

SUBOTICA

DJERDAP

S.MITROVICA

POZEGA

NIS

KOSOVO B

PRIZREN

ZEMLAK

ELBASAN

FIERZA

VAU DEJES

TREBINJE

MOSTAR

TUZLA

UGLJEVIK

VISEGRAD

SARAJEVO

GRADACAC

PLAT

PRIJEDOR

MEDJURICDJAKOVO

KONJSKO

ZAKUCAC

MRACLIN

CIRKOVCE

KRSKOZERJAVINEC

HEVIZ

TUMBRI

MELINE

ERNESTINOVO

DIVACA

PODGORICA

PIVA

FLORINA

BITOLA

PEHLIN

PERUCICA

BA B.BASTA

PLJEVLJA

RIBAREVINE

GALATINA

REDIPUGLIA

WIEN SUDLEVICE

NEUSIEDL

GYORGOD

TISZALOK

KISVARDA

ZAPADOUKRAINSKA

ALBERTIRSA

OBERSIELACH

SAJOSZEGED

MUKACHEVOGABCIKOVO

PODLOG

ROSIORI

PADRIANO

KAINACHTAL

MARIBOR

Source: Uncertainties in the South East European Transmission Network and Evaluation of Risk For Future Infrastructure Investments, ENERGY INSTITUTE HRVOJE POZAR, Zagreb, Croatia and EKC, Belgrade, Serbia, supported by USAID under SECI PROJECT GROUP ON REGIONAL TRANSMISSION SYSTEM PLANNING

According to some studies7 none of the observed interconnection candidate lines proposed by local TSOs bring significant improvement to exchange possibilities in the region. In other words, the SEE transmission grid in 2015 can support planned injection of power from new power plants even without any new interconnection transmission lines. Exchange possibilities in the region are limited by the bottlenecks in internal networks, mainly in Albania, Romania and Bulgaria. Some of these bottlenecks can be removed by applying operational and dispatching control remedial measures. This is the most indicative proof that the existing level of interconnections in the region is satisfactorily high for future foreseen generation investments and exchange patterns, i.e. current congestions can be effectively solved by adequate changes in the transmission system operation. The future need for the development of the transmission networks will be influenced by following uncertainties: Power plant construction (location of the new major TPPs and development of wind power

plants); Connection to Italian/Turkish Market (HVDC cables MN-IT and Romania-Turkey); Energy and power balances in the region (influence on expected power flows).

The table below shows the most important ongoing and planned projects of interconnections between Balkan power systems.

7 Evaluation of investments in transmission network to sustain generation and market development in SEE;

EIHP, EKC, 2007; and Transmission Network Investment Criteria; EIHP, EKC, 2007.


31

Table 4: On-going and planned projects for interconnection in Balkan region

Name of line Investment

mil. EUR Voltage

kV

Status (completion or earliest year

available)

Elbasan-Tirana (AL) - Podgorica (MN) 92 400 Under construction (2010)

Tirane-Vau Dejes (AL) - Pristina (KO) 119 400 Planned (2015)

Bitola (MK) - Vlore (AL) - Brindisi (IT) unknown 400kV + HVDC

submarine Planned (2015)

Montenegro – Italy unknown HVDC submarine Planned (2015)

Croatia – Italy unknown HVDC submarine Planned (2015)

Source: EIHP

The interconnection project between Pristina and Tirana is related to the possible construction of new coal based power plants in Kosovo that would sell electricity to Albania and further to Italy (depending also on a possible submarine connection between Albania and Italy). This submarine cable connection will allow for the transmission of electricity to the Italian market (with higher prices compared to the SEE area). This project is closely related to the possible construction of new major generation facilities in Albania – nuclear power plants, coal power plants (imported coal), gas power plants (TAP8 or LNG9 based) and wind power plants. The submarine cable connection between Montenegro and Italy is also very important as it will allow the supply of electricity from Kosovo to Italy and will connect the SEE and Italian electricity markets, as will the cable linking Croatia and Italy. The reason for the interest of developers in submarine connections between the SEE area and the Italian market is the potential for buidling new generation capacities in SEE (coal, gas and nuclear based), and selling the electricity it to meet the high demands in Italy at generally higher prices than those found in the SEE area.

2.1.6. ELECTRICITY DEMAND IN BALKAN REGION UP TO 2030

For the purposes of this study, electricity demand in the Balkan region up to 2030 was estimated using a bottom-up methodology, by examining different consumer categories. The total electricity demand was further adapted by taking into account transmission and distribution losses.

Table 5: Estimated total electricity demand in the Balkan region up to 2030 TWh 2010 2015 2020 2025 2030

Croatia 16.6 18.2 20.8 23.9 27.0

Bosnia and Herzegovina 11.3 12.8 15.2 17.4 19.5

Serbia 27.5 30.2 33.6 37.3 41.8

Montenegro 3.7 3.9 4.3 4.9 5.5

Kosovo 4.4 5.5 6.6 7.7 9.0

Albania 6.0 7.6 9.6 11.7 14.0

Macedonia 6.6 7.6 8.8 9.9 10.8

Total 76.1 85.8 98.8 112.7 127.6

Source: EIHP

The objective of this analysis was to prepare electricity demand data as an input to the techno-economic model. This increase in total electricity deamnd must be met by the construction of new

8 Trans Adriatic Pipeline (regional natural gas supply project).

9 LNG (Liquefied Natural Gas) – possible location of LNG terminal in Albania.


32

power plants. Additionally, large number of thermal power plants will be decommissioned by 2030 and will therefore have to be replaced by new units. The figure below shows total electricity demand to be represented in the techno-economic model.

Figure 9: Estimated total electricity consumption in the Balkan region until 2030

Source: EIHP

At the beginning of the period countries in the Balkan region are at different starting positions in terms of their economic development. Electricity demand will continue to increase and the gap between current supply and future demand will have to be closed by the construction of new generation capacities, as importing from surrounding markets is not a likely long-term option due to the limited production capacities and increasing prices, which will give additional incentives for investment in local facilities.

2.1.7. POWER GENERATION EXPANSION POSSIBILITIES IN BALKAN REGION – SUMMARY

To understand how this gap can be closed, the different energy technology options that are available in the region must be examined and input in the model as technical possibilities. The main generation expansion options in the region are coal-based thermal power plants and large scale hydro power plants. Larger use of natural gas in electricity generation is limited by the lack of gas transport and distribution networks. Only Croatia and the northern part of Serbia have suitable gas supply routes. However, it is expected that by 2020 gas networks will be well developed in the region as all countries are considering gasification as an option (subject to the development of large scale gas supply routes from Russia and/or the Caspian area). The largest coal reserves are available in Kosovo, followed by Serbia and Bosnia and Herzegovina. These jurisdictions have coal reserves which could be developed and allow for electricity export. If Kosovo is to aggressively develop its coal reserves this should be accompanied by a timely development of the transmission network and connection to other markets (primarily Italian). Montenegro and Macedonia have coal reserves which can be used to satisfy domestic demand. Croatia and Albania have access to the sea and so coal power plants could be based on imported hard coal. Croatia already has 300 MW of power generation at the coast and another 500 MW unit is planned for completion by 2016 (and additional total power of 1000 MW by 2030). Albania is considering joint-venture projects and there is a possibility of developing coal power plants and a submarine cable to Italy.

0

20

40

60

80

100

120

140

2010 2015 2020 2025 2030

TW

h

MK

AL

KO

MN

RS

BA

HR

~50 TWh


33

Several countries in the region have expressed their interest in nuclear power (Croatia, Albania and Macedonia). If this option is to be exercised in the future, it is estimated that the first nuclear unit(s) could be online by around 2025.

Table 6: Indicative hydro potential in the Balkan region

Country Hydro Capacity

MW Energy GWh

Average capacity factor %

Albania

Large 888 2885 37

Small 200 600 34

Total 1088 3485 37

Kosovo

Large 293 398 16

Small 64 294 53

Total 357 692 22

Macedonia Large 956 2116 25

Total 956 2116 25

Montenegro

Large 398 933.7 27

Small 50 110 25

Total 448.4 1043.7 27

Croatia

Large 300 900 34

Small 200 438 25

Total 500 1338 31

Serbia*

Large 1080 3311 35

Small 500 1139 26

Total 1580 4450 32

Bosnia and Herzegovina*

Large 1600 4719 34

Small 200 473 27

Total 1800 5192 33

Region total

Large 5515 15263 32

Small 1214 3054 29

Total 6729 18316 31

* Part of hydro potential shared between Serbia and Bosnia and Herzegovina.

Source: EIHP

The interest of foreign investors in developing wind projects in the region is significant. Countries with defined feed-in tariff systems have registered a large number of projects in the pipeline. In Croatia there is interest of up to 5000 MW10, while the national strategy has envisaged 1200 MW from wind by 2020. In Bosnia and Herzegovina wind potential is estimated at 1000 MW, and in Serbia at 1300 MW. For Albania, optimistic estimations state that approximately 1350 MW of wind power could be constructed with a resulting production of 3000 GWh/yr. The interest of Italian investors is significant and includes construction of wind power plants and submarine cable(s) for transmission of electricity to the Italian market. In Macedonia a Preliminary Atlas of wind was drafted (in 2006) and about 20 locations have been identified, each with the potential of 25 to 33 MW (making 500 to 660 MW of wind potential in total). Data on wind potential in Kosovo are not currently available. According to the Montenegrin Energy Strategy, wind will not play the major role in their electricity balance, with up to only 60 MW of installed capacity by 2020, and an additional 60 MW by 2030. The average capacity factor for wind power plants in the region has been estimated at 25% or at 2200 hours of full capacity utilization during a year.

10

Total capacity of all requests from project developers in the national renewable registry.


34

Other options include use of geothermal energy, waste and biomass for electricity production (and/or for heating).

2.1.8. CO2 EMISSION SOURCES FROM POWER GENERATION IN BALKAN REGION – SUMMARY

The following table summarizes the existing (operational) CO2 emitting power plants in the Balkan region (coal, gas and oil fuelled). Indicative operational hours for existing units are presented in the table below were calculated based on historical data (where available) or were estimated based on the expected role of the unit in the system operation. There are a number of very old units, such as those installed during 1960’s that have low efficiencies, but are still operational. In this table those units were treated as system cold reserve (meaning they were assigned zero or very low operation hours in the model). Regarding the rehabilitation,11 in the table, "no" means that there is no information on specific rehabilitation of a unit, but it is expected that the unit will be decommissioned in the year indicated and that the construction of a new unit is possible (but characteristics of any new unit are not currently known) as in most cases fuel and a suitable site for a power plant are still available in the same location. Conversely, "yes" means that there are plans to rehabilitate the existing units and prolong their operational life. At present, the largest source of CO2 emissions from the power sector is in Serbia (approximately 25 Mt/CO2 per year), followed by Bosnia and Herzegovina (10.5 Mt/CO2 per year) and Kosovo (6.4 Mt/CO2 per year). In these jurisdictions the power generation is coal based. In Croatia CO2 emissions from power generation is also high (approximately 5.9 Mt/CO2 per year), but it is diversified between different fuels and several smaller scale emission points. However a significant point source of emissions from coal plants is located on the coast emitting around 2 Mt/CO2 per year. Macedonia also has significant emissions of approximately 5.2 Mt/CO2 per year, which is mainly attributed to one location, in Bitola. The total expected annual emission from power generation in the Balkan region is 55.2 Mt of CO2, of which 50.5 Mt is attributed to coal based generation.

11

Here "rehabilitation" refers to the rehabilitation of the existing plant, no CCS addition.


35

Table 7: Electricity production capacities and operational conditions in a reference year(2010)

Jurisdiction Plant name

Technology Main fuel Net capacity

MW Indicative

operational hours Electrical efficiency

% CO2 emission

Mt/yr Expected

decommissioning Rehabilitation

Albania

Vlore CCGT oil/gas 100 6500 47 0.33 beyond 2030 -

Total 100 0.33


Tuzla 3 PC coal-lignite 85 4000 25.0 0.49 2013 no

Tuzla 4 PC coal-lignite 175 6000 29.6 1.27 2018 no

Tuzla 5 PC coal-lignite 180 6000 29.5 1.31 beyond 2020 no

Tuzla 6 PC coal-lignite 190 6000 30.5 1.34 beyond 2020 no

Kakanj 5 PC coal-lignite 95 6000 30.8 0.66 2018 no

Kakanj 6 PC coal-lignite 85 6000 24.9 0.73 beyond 2020 no

Kakanj 7 PC coal-lignite 205 6000 29.4 1.50 beyond 2020 no

Gacko PC coal-lignite 237 6000 31.3 1.62 2023 yes

Ugljevik PC coal-brown 244 6000 31.6 1.57 2022 yes

Total 1496 10.48

Croatia

TETO Zagreb* CCGT oil/gas 422 6500 45 1.34 beyond 2020/2030 No

ELTO Zagreb* OC/ST oil/gas 90 4000 35 0.23 2011/2019 No

Sisak 1 ST oil/gas 198 4000 34.3 0.51 2015 No

Sisak 2 ST oil/gas 198 4000 34.3 0.51 2021 No

Rijeka ST oil/gas 303 4500 36 1.04 2022 No

Plomin 1 PC coal-hard 98 6500 32 0.66 2015 No

Plomin 2 PC coal-hard 192 7500 36 1.33 beyond 2030 No

TETO Osijek ST oil/gas 42 4000 30 0.12 2017 No

PTE Osijek OC Gas 48 4000 26.7 0.14 2019 No

KTE Jertovec OC Gas 78 1000 31.3 0.05 2018 No

Total 1669 5.94

Kosovo

Kosovo A3 PC coal-lignite 120 4500 24.1 0.80 2015 No




36



MW Indicative


% CO2 emission

Mt/yr Expected


Kosovo B1 PC coal-lignite 265 6500 30.8 1.99 2024 No

Kosovo B2 PC coal-lignite 260 6500 30.8 1.96 2025 No

Total 895 6.42

Macedonia

Bitola 1 PC coal-lignite 202 7000 35.3 1.43 2021 No



Oslomej PC coal-lignite 112 6000 30.7 0.78 2022 No

Negotino ST Oil 189 1000 34.4 0.15 2020 No

Total 907 5.23

Montenegro

Pljevlja 1 PC coal-lignite 205 6500 32.4 1.47 2027 No

Total 205 1.47

Serbia

Novi Sad 1 ST oil/gas 108 1000 33.3 0.08 new CCGT

Novi Sad 2 ST oil/gas 100 1000 33.3 0.11 new CCGT

TENT A1 PC coal-lignite 191 6500 29.9 1.49 2015 No






TENT B1 PC coal-lignite 580 6500 33.3 4.04 2028 No

TENT B2 PC coal-lignite 580 6500 33.3 4.04 2030 No

Kolubara A1 PC coal-lignite 29 0 24.8 0.00 - No



Kolubara A4 PC coal-lignite 29 0 24.8 0.00 - no

Kolubara A5 PC coal-lignite 100 5000 31.3 0.57 2019 No

Morava PC coal-brown 108 5000 24.8 0.74 2014 No

Kostolac A1 PC coal-lignite 90 0 24.8 0.00 2012 No

Kostolac A2 PC coal-lignite 191 4000 30.8 0.89 2025 No


37



MW Indicative


% CO2 emission

Mt/yr Expected


Kostolac B1 PC coal-lignite 320 5000 33.3 1.71 2027 No

Kostolac B2 PC coal-lignite 320 5000 33.3 1.71 2031 No

Zrenjanin ST oil/gas 111 1000 33.3 0.08 2029 No

Sr. Mitrovica 3 ST oil/gas 29 1000 30.8 0.02 2019 No

Total 4284 25.40

Region Total 9556 55.26

CHAPTER 2 Regional overviews

38

2.2. COUNTRY CASE STUDIES - BALKAN REGION

The following sections give more detailed information on power systems in Balkan area. The data presented below are used as inputs in the techno-economic model.

2.2.1. CROATIA

The following table gives 2008 indicators for Croatia according to IEA statistics.

Table 8: Key indicators for Croatia in 2008

Key indicators

Compound indicators

Population (million) 4.43 TPES/Population (toe/capita) 2.05

GDP (billion 2000 USD) 30.14 TPES/GDP (toe/thousand 2000 USD) 0.30

GDP (PPP) (billion 2000 USD) 67.12 TPES/GDP (PPP) (toe/thousand 2000 USD) 0.14

Energy Production (Mtoe) 3.95 Electricity Consumption / Population (kWh/capita) 3878

Net Imports (Mtoe) 5.51 CO2/TPES (t CO2/toe) 2.31

TPES (Mtoe) 9.08 CO2/Population (t CO2/capita) 4.72

Electricity Consumption* (TWh) 17.20 CO2/GDP (kg CO2/2000 USD) 0.69

CO2 Emissions **(Mt of CO2) 20.93 CO2/GDP (PPP) (kg CO2/2000 USD) 0.31

* Gross production + imports - exports - losses ** CO2 Emissions from fuel combustion only. Emissions are calculated using IEA's energy balances and the Revised 1996 IPCC Guidelines.

Source: IEA

The installed electricity generation capacities in the Republic of Croatia include hydro and thermal power plants owned by the HEP Group (Croatian Power Company), a certain number of industrial power plants and a few privately owned power plants (wind power plants, small hydro power plants). The electricity generation portfolio within the HEP Group consists of 16 hydro power plants, 7 thermal power plants and one half of the installed capacities of the nuclear power plant Krško (located in the territory of Slovenia). Thermal power plants are gas-fired, coal-fired and fuel oil fired. The majority owner over the generation capacities in the Republic of Croatia is HEP Group. The facilities that are not fully owned by HEP are the following: NPP Krško Ltd (nuclear power plant) under the joint ownership of the HEP (50%) and the

Slovenian company ELES GEN Ltd (50%). TPP Plomin Ltd (coal) under the joint ownership of the HEP (50%) and the German

company RWE Power (50%). HEP Generation Ltd won a management and operation and maintenance contract for the plant.

Total available capacity of all HEP’s power plants in the Republic of Croatia amounts to 3 769.2 MW. Total capacity serving the needs of the Croatian electric power system amount to 4 117.2 MW (with 50% of NPP Krško). Of this, 1 681 MW is from thermal power plants (including TPP Plomin and excluding NPP Krško), 2 088.2 MW from hydro power plants and 348 MW in the nuclear unit Krško (50% of total available capacity in this plant). These capacities do not include generating units in other jurisdictions from which the Croatian electric power system has the right


39

to withdraw electricity on the basis of capacity lease and share-ownership arrangements. The capacities in other countries are the following: Thermal power plant Gacko (Bosnia and Herzegovina) – total installed capacity of 300 MW,

coal-fired. Legal basis – shared ownership (1/3 of capacity and power for a 25 year period). Thermal power plant Obrenovac (in the Republic of Serbia) – installed capacity 305 MW,

coal-fired. Legal basis – capacity and power lease on the basis of a credit for construction. The capacity and power from the above-mentioned facilities is not available, as the status of these facilities has not been resolved yet. The open issues regarding the agreements on investments in these facilities refer to the duration period, the way of treatment of the invested funds and what pricing methods should be applied to electricity deliveries.

Table 9: Electricity generation capacity in Croatia (HEP Group ownership)

Plant type Available power

[MW] Capacity share

[%]

Hydro power plants (HPP) 2 088.22 51

Thermal power plants (TPP) 1 489 36

TE Plomin Ltd. (coal) 192 4.6

Total in the Republic of Croatia 3 769.22 91.6

Nuclear power plant Krško (NPP Krško) – 50% 348 8.4

Total 4 117.22 100

Source: EIHP

In 2010 a hydro power plant of 48 MW and a CHP CCGT plant (110 MW) were commissioned. Industrial power plants include units within the industrial installations which are connected to the transmission or distribution grid. Industrial power plants generate electricity/heat/mechanical energy for use in industrial processes, while the electricity surplus can be sold to the grid. These power plants are not a part of the HEP Group, but they have purchase agreements and can deliver the power they produce into the power system. Total installed capacity of industrial power plants amounts to about 210 MW. Beside industrial power plants there is approximately 23 MW of installed capacity for electricity generation in private ownership. Croatia is a net importer of electricity. Excluding generation of NPP Krško, Croatia imports approximately 20% of total annual consumption. About one third of imported electricity is hydro based. According to the National Energy Sector Development Strategy, future electricity in Croatia will be based on hydro (with a remaining potential of 300 MW and 900 GWh), coal (imported hard coal, with several units under consideration), natural gas and wind (investors have expressed interest in up to 5000 MW of capacity). The Strategy also calls for re-thinking and possible re-activation of the national nuclear program. The Croatian power system is very well connected to the neighboring systems. During 2009 several transmission facilities were put into regular operation, of which the most significant is the reconstructed cross-border 220 kV transmission line Mraclin-Prijedor (Bosnia and Herzegovina). Construction work was completed on the Croatian section of the new cross-border transmission line 2x400 kV Ernestinovo-Pecs (Hungary) and preparatory activities begun for technical inspection and line commissioning.


40

Figure 10: Power transmission system in Croatia

Source: HEP-OPS – Croatian Transmission System Operator

Croatia is an Annex I Party to the United Nations Framework Convention on Climate Change. Croatia signed the Kyoto Protocol on 11 March 1999 and ratified it in 30 May 2007. Under the Kyoto protocol Croatia is obliged to reduce its base year (1990) GHG emission by 5% over the period 2008-2012. Annual CO2 emission from the power sector amount to 5.5 million tons, out of which emissions from coal power plants amout around 2 million tons. Croatia applied for EU membership in 2003, and the European Commission recommended making it an official candidate in early 2004. Candidate country status was granted to Croatia by the European Council in mid-2004. The entry negotiations, while originally set for March 2005, began in October of that year together with the screening process. It is expected that negotiations will be closed in the second half of 2011, while the date for becoming a full EU member country could be set for 2013/2014.

2.2.2. BOSNIA AND HERZEGOVINA

The following table gives the selected 2008 indicators for Bosnia and Herzegovina according to IEA statistics.


41

Table 10: Key indicators for Bosnia and Herzegovina in 2008

Key indicators

Compound indicators




Energy Production (Mtoe) 4.34 Electricity Consumption / Population (kWh/capita) 2467


TPES (Mtoe) 5.99 CO2/Population (t CO2/capita) 5.18

Electricity Consumption* (TWh) 9.31 CO2/GDP (kg CO2/2000 USD) 2.32



Source: IEA

The Bosnia and Herzegovina electricity market is split into three main companies, each supplying customers in a certain area. These companies own and operate generation and distribution/supply facilities, while transmission system development and operation are separate companies. Total installed power in Bosnia and Herzegovina is 3,608 MW. Of this, 55% is from large hydropower and 44% from thermal power plants, while the remaining 1% is from small hydropower and industrial plants. All thermal power plants use coal from the local coal mines (low calorific lignite and/or brown coal). The average annual production is about 13.4 TWh (hydropower accounts for 44%, thermal power for 55% and other power plants for 1%). The current level of generation is sufficient to cover the total electricity consumption in Bosnia and Herzegovina, while surpluses are exported to neighboring systems. Of the countries included in this study, Bosnia and Herzegovina is the only net electricity exporter.


42

Table 11: Existing power plants in Bosnia and Herzegovina

Company and ower plant type

Capacity MW

Capacity share %

Average annual generation

GWh

Share in generation

%

EP HZHB

HPP 747 100.0 1 569 100.0

Total EP HZHB 747 20.8 1 569 11.7

EP BIH

HPP 504 32.1 1 515 24.9

TPP (Coal) 1 033 67.1 4 500 74.0

Small HPP 13 0.8 65 1.1

Total EP BIH 1 550 42.8 6 080 45.4

ERS

HPP 742 56.6 2 861 49.9

TPP (Coal) 555 42.3 2 800 48.8

Small HPP and industrial plants

14 1.1 72 1.3

Total ERS 1311 36.4 5 733 42.8

Total power system of Bosnia and Herzegovina

HPP 1 993 55.1 5 945 44.4

TPP 1 588 44.1 7 300 54.6

Small HPP and industrial plants

27 0.8 137 1.0

Total Bosnia and Herzegovina

3 608 100.0 13 382 100.0

Source: EIHP

Existing hydropower plants are expected to remain in operation until the end of the planning horizon (i.e. at least until 2030, subject to regular maintenance and planned rehabilitation). Existing thermal units were built over the period 1966 - 1988, and so most of the units have been in operation for more than 25 years. Some of them are therefore planned to be decommissioned or replaced before 2020, and the rest by 2030. These decommissionings are taken into account in the techno-economic modeling excercise. Despite the fact that Bosnia and Herzegovina is currently self-sufficient in terms of meeting electricity demand, taking into account the expected increase in electricity demand and the decommissioning of existing thermal power plants in the near future, one can expect a reduction of excess electricity in the system, which will lead to a reduction of exports. Ultimately there will be a need to build new power plants (or the need to import from other systems) to meet the demand for electricity. The total potential for construction of new power plants in Bosnia and Herzegovina is greater then 7000 MW, i.e. more than 30 TWh/year. The confirmed potential, therefore, exceeds installed capacities of existing power plants by more than 100%, while annual potential in electricity generation is 2.5 times larger compared to current level.


43

Table 12: Potential for development of power generation in Bosnia and Herzegovina

Company/Plant type Power

Share in capacity

Average annual generation

Share i generation

MW % GWh %

EP HZHB

HPP 213 15,1 491 9.0

TPP (lignite) 530 37.7 3 000 55.2

Wind 624 44.4 1 756 32.3

Small HPP 40 2.8 186 3.4

Total EP HZHB 1 406 19.9 5 433 17.6

EP BIH

HPP 157 10.5 481 5.0

TPP (lignite, brown coal) 1300 87.2 9 100 93.7

Wind 0 0.0 0 0.0

Small HPP 34 2.3 127 1.3

Total EP BIH 1 491 21.1 9 708 31.4

ERS

HPP 2 014 66.1 5 111 48.4

TPP (lignite) 819 26.9 4 801 45.5

Wind 0 0.0 0 0.0

Small HPP 212 7.0 651 6.2

Total ERS 3 045 43.1 10 563 34.1

Other – private investors

HPP 729 2 234

TPP (lignite) 389 3 000

Total other 1 117 15.8 5 234 16.9

Total Power System of Bosnia and Herzegovina

HPP 3 112 44.1 8 317 26.9

TPP 3 038 43.0 19 901 64.3

Wind 624 8.8 1 756 5.7

Small HPP 286 4.1 963 3.1

Total Bosnia and Herzegovina

7 060 100.0 30 937 100.0

Source: EIHP

Bosnia and Herzegovina is very well connected to the neighboring systems and there are plans for local power companies to develop new generation capacities based on locally available coal (mainly lignite) and to export electricity. The most advanced project is the construction of a 300 MW privately financed coal power plant at Stanari.


44

Figure 11: Power transmission system in Bosnia and Herzegovina

Source: Elektroprenos BIH – Bosnia and Herzegovina Transmission System Company

Bosnia and Herzegovina ratified UNFCCC in September 2000 and is a Non-Annex I party to the UNFCCC. The Kyoto Protocol was ratified by Bosnia and Herzegovina in July 2007. In May 2010, Bosnia and Herzegovina has submitted the initial national communication under the UNFCCC. Current annual CO2 emission from the power sector is estimated at approximately 9 million tons. The accession of Bosnia and Herzegovina to the EU faces economic and political problems today. Negotiations on a Stabilisation and Association Agreement, the first step before applying for membership, began in 2005. Negotiations stalled due to a disagreement over the required reforms. The EU has stated that Bosnia and Herzegovina cannot submit an application for membership until the Office of the High Representative (OHR) in Bosnia and Herzegovina, which is charged with implementation of the Dayton Peace Agreement, has been closed.

2.2.3. SERBIA

The following table gives the 2008 indicators for Serbia according to IEA statistics.


45

Table 13: Key indicators for Serbia in 2008

Key indicators

Compound indicators

Population (million) 7.35 TPES/population (toe/capita) 2.18



Energy production (Mtoe) 9.92 Electricity consumption / Population (kWh/capita) 4284

Net imports (Mtoe) 6.38 CO2/TPES (t CO2/toe) 3.07

TPES (Mtoe) 16.03 CO2/population (t CO2/capita) 6.69

Electricity consumption* (TWh) 31.49 CO2/GDP (kg CO2/2000 USD) 3.55

CO2 emissions **(Mt of CO2) 49.21 CO2/GDP (PPP) (kg CO2/2000 USD) 0.96

* Gross production + imports - exports - losses ** CO2 Emissions from fuel combustion only

Source: IEA

Power plants in Serbia are operated by the national power company EPS. The total (net) capacity of EPS's electric power generating facilities is 8,355 MW:12 The installed capacity of lignite-fired thermal power plants is 5,171 MW. The installed capacity of hydro power plants 2,831 MW. The installed capacity of oil-fired and natural gas-fired combined heat and power plants is

353 MW. The Serbian national power company (EPS) also operates three power plants having a net

capacity of 461 MW which are owned by municipalities and/or different industrial companies.

Lignite power plants are: TPP Nikola Tesla A – 6 units – total available capacity of 1,502 MW and annual generation

of 7,200 GWh. TPP Nikola Tesla B – 2 units – total available capacity of 1,160 MW and annual generation

of 7,700 GWh. TPP Kolubara – 5 units – total available capacity of 245 MW and annual generation of

1,150 GWh. TPP Morava – one unit – total available capacity 108 MW and annual generation of

341 GWh. TPP Kostolac A – 2 units – total available capacity of 281 MW and annual generation of

720 GWh. TPP "Kostolac B" – 2 units – total available capacity of 640 MW and annual generation of

3,000 GWh. Other thermal units include: CHP Novi Sad – 2 units – total available capacity 208 MW (fuel oil or natural gas). CHP Zrenjanin – one unit – total available capacity 100 MW. CHP Sremska Mitrovica – 3 units – total available capacity 45 MW.

Total capacity of CHPs is 353 MW and their total annual production amounts to 350 GWh.

12

This value includes TPP Kosova A and B (lignite) in Kosovo. As of 1 July 1999, EPS no longer operates these facilities.


46

The units at TPP Nikola Tesla with a total 3,015 MW of available capacity make up 36% of the total capacity of the electric power system of Serbia. The expected annual generation of TPP Nikola Tesla is 16,400 GWh which contributes around 47% of the total production of the EPS. TPP Nikola Tesla uses lignite from the Mining Basin Kolubara. Units at TPP Kostolac with a total available capacity of 921 MW make up 11% of the total available capacity of the electric power system of Serbia. Electricity generation from TPP Kostolac of 3,700 GWh makes up almost 11% percent of the total electric power production in EPS's system. These units use lignite produced at open-pit mines Cirikovac and Drmno. TPP Kostolac A also supplies heating to the cities of Kostolac and Pozarevac. The total capacity of the nine hydro power plants with fifty hydro units is 2,831 MW, which accounts for 34% of EPS's total installed capacity. HPP Djerdap with total of 1,537 MW available capacity makes up 18% of the total installed capacity in Serbia. The production of 28 units into four HPPs, amounting to 7,360 GWh makes 21% of the total electric generation in EPS's system (or 67% of the total hydro potential). Units under HPP Drinsko-Limske with a total of 1,083 MW available capacity make up 13% of the total installed capacity in Serbia. Electricity generation from 14 units of this HPP, amounting to 2,937 GWh annually, makes up 27% of the total generation in all hydro power plants, or 8.3% of the total production in EPS's system.

Figure 12: Power transmission system in Serbia

Source: EMS – Serbian Transmission System Operator

Given the relatively old age of the thermal power plants in Serbia, there are plans to develop new coal and gas units:


47

Construction of TPP Kolubara B, 2x350 MW: The development of this plant began back in 1983 (decision on construction), and building started in 1988. By 1992 approximately 40% of the plant was completed, but construction was soon halted due to the economic crisis. In 2004 a feasibility study showed that an additional 550 million Euros (770 million USD) should be invested to allow for the completion of the plant. The expected net efficiency should be 37% (subcritical boiler parameters) and the earliest possible commissioning would be 2014/2015.

Construction of TPP Nikola Tesla B3, new unit: This will represent the second and final phase of the development at the site (next to the existing units 2x620 MW). Construction of a supercritical unit of 700 MW is envisaged with an expected net efficiency of 40%. The total investment is estimated at 870 millions Euros (1 215 billion USD). The earliest commissioning possible in 2015/2016.

CHP Novi Sad: A complete reconstruction of the existing CHP site by development of a modern high efficient CCGT unit of 450 MWe and 300 MWt has been commissioned, with an expected net electrical efficiency of 58%, and total efficiency in cogeneration of up to 83%. The total investment is estimated to be 280 millions Euros (390 millions USD). The earliest year of availability is 2013/2014 and the natural gas will be imported from Russia.

Development of FBC (fluidized bed combustion) coal units in Kolubara mining basin using low-calorific and low quality coal.

There are also plans to further utilize the remaining hydro potential at the Drina river, which is on the border with Bosnia and Herzegovina, and so cooperation between countries would be required to develop a project. There are also plants to utilize hydro potential at the Bistrica river (pumped storage plant). Apart from new construction, there are plans to rehabilitate and increase the generation capacity of the existing HPPs. The potential for development of small HPPs is significant, with 900 locations with a total estimated power potential of 500 MW. Based on existing and available analyses and studies provided by the Ministry of Energy, realistic wind energy potential in Serbia is estimated at 1,300 MW. On November 7th 2007, Serbia initiated the Stabilization and Association Agreement (SAA) with the EU. Serbia officially applied for EU membership on December 22nd 2009. To enter into force SAA must be ratified by all EU member states and this process is underway. It is expected that the SAA will enter into force in 2011. In November 2010 the European Commission presented a Legislative questionnaire to Serbia, and in January 2011 Serbia responded to the questionnaire. Serbia is a non-Annex I party to the UNFCCC. The UNFCCC was ratified by Serbia in March 2001, while the Kyoto Protocol was ratified in October 2007. In November 2010 Serbia submitted its first national communication under the UNFCCC. Total annual CO2 emission from coal power plants (excluding units in Kosovo area) is estimated at approximately 25 million tons.

2.2.4. KOSOVO

For Kosovo, general data about GDP, population and other indicators are not available from IEA, and so data from the Energy Community is given below.


48

Table 14: Key indicators for Kosovo in 2008 (2005)

Key indicators

Population mid-2008 (million) 2

GDP 2008 (billion 2008 USD) 5.6

TPES 2005 (Mtoe) 2.4

Energy Production 2005 (Mtoe) 1.2

Net Imports 2005 (Mtoe) 1.2

Electricity Consumption* 2008 (TWh) 3.98

CO2 Emission** Estimated (Mt of CO2) 11.3

Compound indicators

Electricity Consumption / Population 2008 (kWh/capita) 1990

CO2/TPES Estimated (t CO2/toe) 4.71

CO2/Population Estimated (t CO2/capita) 5.65

CO2/GDP Estimated (kg CO2/2008 USD) 2.02

* Gross production + imports - exports - losses ** CO2 Emissions from fuel combustion only. Emissions are calculated using IEA's energy balances and the Revised 1996 IPCC Guidelines

Source: Energy Community, EIHP

The main energy resource in Kosovo is coal. Coal is used for electricity production and in industry. Electricity is produced in two aged and inefficient power plants – TPP Kosova A and TPP Kosova B. Total installed capacity of TPPs is 1,524 MW, but only 951 MW is available due to their inefficient operation. One large and several small hydro power plants (connected to the distribution network) are also in operation. The characteristics of these plants are given in the table below. Due to the lack of investment in generation facilities, existing power plants are in poor condition and there are plans for their rehabilitation (some units have already been rehabilitated), as well as plans for opening a new coal mine. After their rehabilitation, the generation capacity should be substantially increased. Kosovo is a net importer of electricity and load shedding is applied regularly. About 10% of total demand is covered by electricity imports. The level of technical and non-technical losses in the distribution is rather high (approximately 40%) and the collection rate is very low (around 80%).


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Table 15: Installed capacities in the Kosovo power system

Plant / Unit

Installed capacity

MW

Available capacity

MW

Comission year

Expected decommission

year

Availability %

Efficiency %

TPP Kosova A

A1 65 35 1962 2008 53.6 21

A2 125

A3 200 110 1970 2011 75 21

A4 200 110 1971 2012 75 21

A5 210 110 1975

Total 800 365

TPP Kosova B

B1 339 270 1983 2027 79 34

B2 339 270 1984 2027 79 34

Total 678 540

Plant /

Unit

Installed capacity

MW

Available capacity

MW

Comission year

Expected decommission

year

Availability %

Generation GWh

HPP Ujmani

U1 17.5 17.5 1981 2033 95 55.8

U2 17.5 17.5 1981 2033 95 55.8

Total 35 35 111.6

Small HPPs in distribution network

Total 11.82 11.82 38.0

Total 1524.8 951.8

Source: EIHP

The Kosovo lignite mines are among the most favorable lignite deposits in Europe due to the geological conditions. With an average stripping ratio of 1.7 m3 of waste to 1 ton of coal, coal production at Kosovo mines could be supplied at very competitive prices compared to international fuel sources. The total estimated economically exploitable resources of approximately 10,000 Mt represent one of the richest lignite sources in Europe. Kosovo is expected to use lignite as its main source of energy for at least the next 40 years. There are plans to develop around 1,000 MW of new coal power units in Kosovo by 2020 (the first phase of the Kosovo e Re Power Plant project is expected to be operational by 2016/2017, and will be 560 MW). There are plans to further exploit the limited hydro resource in Kosovo with the construction of a new two-step cascade HPP Zhur with total installed power of 292.8 MW and average annual generation of 398.2 GWh. The basic step is HPP Zhur I with rated capacity of 246 MW and average annual generation of about 335 GWh. HPP Zhur II is the lower step, with rated capacity of 46.8 MW, utilizing the remaining head with an average annual generation of 63 GWh. The potential HPP has the characteristics of a peaking plant with large storage capacity (which amounts to nearly 40% of the annual natural inflow). Currently there are in total 128 MW of issued/authorized requests for construction of wind power plants.


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Figure 13: Power transmission system in Kosovo

Source: KOSTT – Kosovo Transmission System Operator

Accession of Kosovo to the EU faces economic and political problems, the largest being the fact that several EU states which would need to ratify its eventual accession do not recognize it as a state but as a province of Serbia under United Nations protection, mandated by the United Nations Security Council Resolution 1244. As of January 2010, 22 of the 27 member states recognize Kosovo as an independent state. The European Parliament adopted a resolution in July 2010 calling on all member states to recognize Kosovo. Kosovo (under UNSCR 1244) is officially considered a potential candidate by the EU. Kosovo is the only jurisdiction in the Balkan region that is not a member to the UNFCCC/Kyoto Protocol, even though it is obliged to participate according to the Energy Community Treaty. This issue is also closely related to, and has a negative influence on, the transaction process for a new coal power plant. The Assembly of Kosovo has passed around 40 laws that are relevant in some way to fighting climate change, many of which adhere to international standards, although they are mostly unimplemented. It is estimated that Kosova A and Kosova B emit about 6 million tons of CO2 annually.

2.2.5. MONTENEGRO

For Montenegro, general data about GDP, population and other indicators are not available from IEA, and so data from the Energy Community is given in the table below.


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Table 16: Key indicators for Montenegro in 2008 (2005)

Key indicators

Population mid-2008 (million) 0.62

GDP 2008 (billion 2008 USD) 4.9

TPES 2005 (Mtoe) 1

Energy production 2005 (Mtoe) 0.6

Net imports 2005 (Mtoe) 0.5

Electricity consumption* 2008 (TWh) 3.86

CO2 Emission** Estimated (Mt of CO2) 2.6

Compound indicators

Electricity consumption / population 2008 (kWh/capita) 6225

CO2/TPES estimated (t CO2/toe) 2.60

CO2/population estimated (t CO2/capita) 4.19

CO2/GDP estimated (kg CO2/2008 USD) 0.53

* Gross production + imports - exports – losses. ** CO2 Emissions from fuel combustion only.

Source: Energy Community, EIHP

Generation, distribution and supply assets in Montenegro are owned and operated by EPCG, a national power company. The total installed generating capacity of power plants is 868 MW, of which 685 MW (76%) is from hydro power plants (two main locations and several small HPPs) and 210 MW (24%) comes from the thermal power plant (commissioned in 1982 and fuelled by domestic lignite). One quarter to one third of total annual needs for electricity is satisfied from imports. The supply side is heavily influenced by a large share of direct, industrial consumers, such as steel and aluminum factories, accounting for about 30% of total electricity consumption. There are plans to further develop coal reserves, including construction of the second unit at the Pljevlja site (approximately 225 MW) and the development of two more coal mine locations – Maoče (400 MW) and Berane (110 MW). The possibility of exploiting the hydropower potential of the River Morača through a cascade of hydropower plants upstream of Podgorica has been investigated since the 1950s. Over the years, detailed plans and preparations have been made, which resulted in the development of a basic technical solution with four dams. Comprehensive updates to the project feasibility studies were made in 1998. The existing basic technical structure that motivated the Montenegrin Government to announce an international tender consists of a cascade of four hydropower plants: Andrijevo, Raslovidi, Milunovid and Zlatica, with a total installed capacity of 238 MW and an estimated average annual generation of 721 GWh. It is expected that the project could be completed between 2015 and 2020. The power transmission grid in Montenegro is well developed and consists of 400, 220 and 110 kV lines. Montenegro is well connected to neighboring countries Serbia and Albania. A new 400 kV interconnector with Albania is currently under construction.


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Figure 14: Power transmission system in Montenegro

Source: EPCG AD Niksic – Montenegrin Power Company

Montenegro is a Non-Annex I party to the UNFCCC. It ratified the Convention in March 2006, and subsequently the Kyoto Protocol in June 2007. In October 2010 the initial national communication to the UNFCCC was submitted. The current level of annual CO2 emissions from the only coal thermal power plant is about 1.4 million tons. After Montenegro voted for independence (from Serbia) in May 2006, negotiations for EU accession were launched in September 2006. Montenegro officially applied to join the EU on the 15th of December 2008. In May 2010, the Stabilization and Association Agreement (SAA) between Montenegro and the EU came into force. The European Commission recommended Montenegro as candidate country in November 2010. This candidate status was officially granted in December 2010.

2.2.6. ALBANIA

The following table gives the 2008 indicators for Albania according to IEA statistics.


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Table 17: Key indicators for Albania in 2008

Key indicators

Compound indicators




Energy production (Mtoe) 1.15 Electricity consumption / population (kWh/capita) 1373





* Gross production + imports - exports – losses. ** CO2 Emissions from fuel combustion only. Emissions are calculated using IEA's energy balances and the Revised 1996 IPCC Guidelines.

Source: IEA

In Albania, more than 98% of electricity is generated by hydro power plants that are owned and operated by the state owned company KESH. The most important are the three plants in the Drin River Cascade which produce more than 90% of total electricity generation. The other cascades generate the remaining 8%. There are two thermal power plants: TPP Fieri and TPP Vlore. TPP Fieri (using fuel oil) has been out of operation since April 2007. There are plans to either rehabilitate the plant or construct a new one. TPP Vlore was put into operation in 2010. It is a 100 MW dual fuel unit (marine diesel oil and natural gas, though currently using marine oil). TPP Vlore is used as peaking plant due to high fuel costs. The following table shows the installed hydro capacities in power plants in Albania.

Table 18: Installed hydro power capacities in Albania

River Plant Capacity

MW Generation*

GWh Commissioned

Drin

Fierza 500 1 167 1978

Komani 600 1 704 1985

Vau Dejes 250 874 1971

Mati Ulez 24 99 1957

Shkopeti 25 81 1963

Bistrica Bistrica 1 23 115 1966

Bistrica 2 5.5 26 1967

- Other (SHPP) 35 90 1951-1980

Total 1 462.5 4 156

* - historical average generation

Source: EIHP

As most of the electricity production is hydro based, during the dry seasons the generation is decreased and electricity imports are needed to cover the load. Because of the increasing electricity demand, lack of new generation investments in the last 25 years and constraints on the interconnection lines, the system cannot cover the demand and so it is necessary to carry out load-shedding.


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Albania is one of several net importer countries in the region. In 2007, partly as a result of widespread drought and the domestic reliance on hydro power and the limitations of the transmission lines (all imported electricity must come from Montenegro via two 200 kV lines, or from Greece via 400 kV lines), KESH imported more than 50% of its consumption and was forced to institute rolling blackouts. The situation has improved in 2008 and 2009, with electricity imports estimated at making up approximately 11% of consumption in 2009. Albania has a large hydro potential mostly in the Drin, Vjosa and Devolli river cascades. The country aims to integrate and maximally utilize the energy potential of the Vjosa Cascade (which can reach up to 495 MW) and the Devolli Cascade (up to 320 MW). Moreover, there are number of sites for small hydro plant projects (up to 10 MW) all over the country. Coal is one of the largest energy sources of Albania and it is spread over four main basins. Total forecasted reserves are around 227 Mtoe. Total proven reserves in all basins are around 132 Mtoe. Albanian coal deposits are characterized by low quality, high sulfur content (3-5 %), high ash content (30-60 %) and moisture content of up to 60 %. Coal has a low calorific value of range 8.4-16.4 kJ/kg and is extracted from depths of up to 300 m. Supply and use of coal has declined from approximately 645 ktoe or 22% of the primary energy supply in 1990, to 22 ktoe in 2006. Coal contribution in the Albanian energy market has declined due to the following reasons: The coal extraction technology is very old Coals are of lignite types with low calorific values, high content of sulphur, humidity and

ashes The coal must be extracted from depths of up to 300 m Extraction and enrichment costs are consequently very high High content of sulfur and ashes in the coal would require using scrubbers to lower

emissions, creating higher costs for a generating unit Coal is mainly used in industry and for other heating purposes. Domestic production is very low and there are no plans to increase production due to the reasons given above. In the past, domestic coal was used mainly for electricity generation. However there are plans to use imported hard coal for electricity generation. These projects are closely related to the possible connection with the Italian electricity market. Development of the national nuclear power program is also foreseen as part of the development strategy of the energy sector. The main challenges in the operation of the Albanian power system are: Electricity production is hydro based and highly dependable on hydrology changes System peak load is at the same level as installed capacities, so there is little or no reserve. Security of supply is low Congested tie-lines during peak load hours and dry seasons Load shedding is regularly applied having negative effects on the overall economy and

society Large technical and non-technical losses (~41% of gross consumption in 2006 and ~36% in

2007) Low collection rate (<90%) Lack of investment into generation facilities Albania is a net importer of electricity and imports are expected to increase in the coming

years


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The system is interconnected with neighbouring systems through the lines shown in the following table and figure. Albanian TSO is the only TSO in region that is not member of ENTSO-E13 (former UCTE14). There are plans to connect to the Italian market by a submarine HVDC cable.

Table 19: Interconnection lines between Albania and neighboring power systems

Name of line Type Voltage level [kV]

Fierza (AL) - Prizren (KO) single circuit 220

Vau Dejes (AL) - Podgorica (MN) single circuit 220

Zemblak (AL) - Kardia (GR) single circuit 400

Bistrica (AL) - Igumenice (GR) single circuit 150

Source: EIHP

Figure 15: Power transmission system in Albania

Source: Ministry of the economy, trade and energy; ERE; TSO

Albania applied for EU membership in April 2009. Officially recognized by the EU as a "potential candidate country", Albania started negotiations on a Stabilisation and Association Agreement in 2003. This was successfully agreed and signed in June 2006, thus completing the first major step toward Albania's full membership in the EU.

13

ENTSO-E – European Network of Transmission System Operators for Electricity. 14

Union for Coordination of Transmission of Electricity.


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Albania is a Non-Annex I party to the UNFCCC. The UNFCCC was ratified in October 1994 and Kyoto Protocol in April 2005. The first national communication to the UNFCCC was submitted in September 2002, followed by the second report in November 2009. Direct fuel combustion CO2 emissions from the power sector are negligible. The only thermal power plant in operation was commissioned in 2010 (marine diesel) and it is used as a peaking unit and so is often not in operation.

2.2.7. MACEDONIA

The following table gives the 2008 indicators for Macedonia according to IEA statistics.

Table 20: Key indicators for Macedonia in 2008

Key indicators

Compound indicators










Source: IEA

The main energy resources in Macedonia are coal (lignite) and hydro. Coal is used for electricity generation at two locations – Bitola and Oslomej. The power plants are in very good condition and operate at a high capacity factor. There is one fuel oil thermal power plant which operates from time to time in the case of high demand (variable costs are high due to expensive fuel oil). A CHPP at Skopje (250 MW, natural gas) has also been scheduled to be commissioned sometime during 2010. Installed capacities are presented in the table below.

Table 21: Installed capacity in thermal power plants in Macedonia

Plant / Unit

Installed capacity

MW

Available capacity

MW

Comission year

Year of rehabilitation

Expected generation

GWh

Efficiency %

TPP Bitola / lignite

1 225 202.5 1982 1994 35.3

2 225 202.5 1984 1994 35.3

3 225 202.5 1988 1994 35.3

Total 675 607.5 4400-4600

TPP Oslomej / lignite

1 125 112.5 1989 550-700 30.7

TPP Negotino / lignite

1 210 189 1978 1200-1400 34.4

TPP Total 1010 909 6150-6700

Source: EIHP


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Table 22: Installed capacity in hydro power plants in Macedonia

Plant / Site Installed capacity

MW Generation

GWh Comissioned

year Storage mil. m3

HP System Mavrovo

HPP Vrben 12.8 45 1959

HPP Vrutok 172 350 1957/1973 277

HPP Raven 19.2 40 1959/1973

HPP Tikves 116 184 1966/1981 309.6

HPP Spilje 84 384 1969 223

HPP Kozjak 80 156 2004 260

HPP Globocica 42 191 1965 13.2

Total 526 1 350 1 082.8

Source: EIHP

There are domestic coal reserves in Macedonia which are used for electricity production. There are plans to further develop coal as an energy option and to gradually replace the existing coal units sometime after 2020. Units of approximately 300 MW are in consideration. Construction of CCGT units is also planned. Currently natural gas is available only in Skopje, but a recent study on country gasification, completed by the Ministry of Transport and Communication in 2010, estimates that by 2020 there will be two CCGT units in operation, and an additional unit by 2030. There are a number of locations available for the construction of both large and small hydro power plants in Macedonia. The potential of large scale HPPs is estimated at approximately 950 MW. A preliminary Atlas of winds for Macedonia was drafted in 2005 and 2006 and identified about 20 locations each with the potential of 25 to 33 MW (making 500 to 660 MW of wind potential in total). Currently Macedonia is well connected to Kosovo, Bulgaria and Greece. Further expansion of interconnections is expected up to 2015 (400kV connection to Serbia), followed by the same type of connection to Albania. Depending on the future construction of power plants in the Kosovo area, additional interconnections are expected (Kosovo-Macedonia).


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Figure 16: Power transmission system in Macedonia

Source: ELEM – Macedonian Power Company

Macedonia began its formal process of rapprochement with the EU in 2000, by initiating negotiations about the EU's Stabilization and Association Process, and it became the first non-EU country in the Balkans to sign the Stabilization and Association Agreement, in April 2001. In March 2004 Macedonia submitted its application for EU membership. The European Council officially granted the country candidate status in December 2005. Macedonia is a Non-Annex I party to the UNFCCC. The UNFCCC was ratified by Macedonia in January 1998 and the Kyoto Protocol in November 2004. Macedonia's first national communication under the UNFCCC was delivered in March 2003, followed by the second communication in December 2008. Annual CO2 emissions from coal power plants is estimated at 5.5 million tons.

2.3. SOUTHERN AFRICAN REGION

This section presents the main existing and potential emission sources in the power system of the Southern African region. For the purposes of the report, the Southern African region includes the following countries: South Africa, Namibia, Mozambique and Botswana, which are highlighted in the map below. The following sub-sections give an overview of the region in terms of the regional structures and initiatives in place, the main development indicators and an overview of the power system in place (generation capacity, power exchange, network, CO2 emissions) for the four countries.


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Figure 17: Southern African region

2.3.1 BACKGROUND: THE SOUTHERN AFRICAN POWER POOL

The selected countries are a subset of the countries that form the Southern African Power Pool (SAPP). The SAPP is a co-operative of 12 country member utilities (Table 23) that interact at policy, planning and operational levels. SAPP does not own or physically operate generation plants and transmission networks within the region - the national governments and utilities have that responsibility. SAPP furthermore has no responsibility to distribute power in the individual member states. SAPP co-ordinates member interests and attempts to influence the utilities to act in favour of common SADC’s (Southern African Developing Community) policy goals. However the implementation of these goals remains with the individual power utilities and their respective governments.

Table 23: SAPP Membership Full name of utility Status Abbreviation Country

Botswana Power Corporation

Operating Member BPC Botswana

Electricidade de Mocambique

Operating Member EDM Mozambique

Electricity Supply Corporation of Malawi

Non-operating Members ESCOM Malawi

Empresa Nacional de Electricidade

Non-operating Members ENE Angola

ESKOM Operating Member Eskom South Africa

Lesotho Electricity Corporation

Operating Member LEC Lesotho

NAMPOWER Operating Member Nam Power Namibia

Societe Nationale d’Electricite

Operating Member SNEL DRC

Swaziland Electricity Company

Operating Member SEC Swaziland

Tanzania Electricity Supply Company Ltd

Non-operating Members TANESCO Tanzania

ZESCO Limited Operating Member ZESCO Zambia

ZESA Holdings Privately Limited

Operating Member ZESA Zimbabwe


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SAPP organisational structure consists of Environmental, Markets, Operating and Planning sub-committees and a Co-ordination Centre. These are all overseen by a Management committee which is in turn overseen by a multi-country Executive committee. Some visionary aims of SAPP are that the Southern African region be “a region of choice for investment by energy intensive users and to ensure sound economic, environmental and social practices”. SAPP also co-ordinates and enforces regional standards of quality of supply, measurement and monitoring of systems’ performance. The members of SAPP created a common market (Day Ahead Market) for electricity in the SADC region with the intention that their customers benefit from the reliable and economical electricity supply, however, the operations of the market have not commenced yet.

2.3.2 MAIN DEVELOPMENT INDICATORS

The following table shows the main development indicators for the Southern African region.15

Table 24: Key indicators for the Southern African region in 2008 Indicator South Africa Botswana Mozambique Namibia

Population million 48.69 3.77 7.35 0.62

GDP (PPP) billion USD 2000 531.82 34.31 51.08 4.90***

Electricity consumption TWh* 232.23 9.31 31.49 3.86

CO2 emission* million tons/yr 337.42 9.0 26.0 1.4

Kyoto

ratified Conditional Target put

forward under Copenhagen Accord





Source: IEA and ERC

2.3.3 INSTALLED GENERATION CAPACITY – SUMMARY

Table 25 and Figure 18 below show a summary of the installed capacity in the Southern African region. The data shown corresponds to the end of 2009.

Table 25: Available generation capacity in the region

Country HPP TPP NPP Other Total

Peak Load

MW

South Africa 665 39,850 1,800 1,580 43,893 37,611

Botswana 0 120 0 0 120 434

Mozambique 2,140 90 0 0 2,230 481

Namibia 249 144 0 0 393 445

Total 2,954 40,204 1,800 1,580 46,500 38,958

Source DOE IRP, Power Pool Plan

The total available capacity for the region is approximately 46.5 GW, most of which is coal fired and in South Africa. Mozambique has the most hydro capacity, more than half of which is exported to South Africa. Note that the Mozal smelter is accounted for in the South African demand, as it is

15

Southen African region as defined in this report (South Africa, Botswana, Mozambique, Namibia).


61

currently supplied by Eskom. Both Namibia and Botswana rely on import capacity to meet their peak demand. South Africa’s reserve margin is less than the targeted 15%, and so is and will remain in a vulnerable position until the new coal power station comes online in 2012-2013. Although Mozambique appears to have excess capacity, the limited transmission grid infrastructure causes a bottleneck between supply and demand.

Figure 18: Structure of installed capacity for Southern African countries

2.3.4 ELECTRICITY CONSUMPTION, PRODUCTION AND EXCHANGE IN THE SOUTHERN AFRICAN REGION - SUMMARY

The table below summarises the electricity consumption, production and net imports in the Southern African region. Here again, the largest share of generation is in South Africa, accounting for almost 95% of total generation. Most of this generation comes from coal fired plants.

Table 26: Summary of electricity consumption, production and exchange in Southern Africa Country Utility Consumption

(sales) Generation

Sent out Net

Imports16

GWh GWh GWh

Botswana BPC 2815 657 2,572

Mozambique EDM 1,380 11,220 -9,646

Namibia NamPower 3,259 1,576 2,045

South Africa Eskom 224,367 239,108 -3,128

2.3.5 POWER TRANSMISSION NETWORK IN THE REGION – SUMMARY

Error! Reference source not found. is a map of the region showing the existing transmission nfrastructure (in blue) and forthcoming transmission projects (in dotted red). Bulk power transfers in the SAPP transmission grid occur at 765 kV, 400 kV, 330 kV, 220 kV, and 132 kV AC. A DC link, +533 kV, connects Songo near HCB in Mozambique with Eskom’s Apollo substation in South Africa.

16

Negative values showing net exports.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Botswana Mozambique Namibia South Africa

Shar

e o

f In

stal

led

Cap

acit

y

Pump Stor

Hydro

Nuclear

Oil/Gas

Coal


62

The 765 kV Eskom system extends from the coal fields in north-east of South Africa towards Cape Town in the south-west. Eskom’s 400 kV system connects through Botswana to Zimbabwe, to Namibia, and to Mozambique directly and via Swaziland. Eskom also connects to Namibia and Mozambique at 220 kV, and to Botswana, and Mozambique at 132 kV.

Figure 19: Power Transmission System for the SAPP

Source: African Power Pools and Interconnectors. Eskom Web Site. Web accessed 17 February 2011

2.3.6 ELECTRICITY CONSUMPTION IN THE SOUTHERN AFRICAN REGION UP TO 2030

The table below gives an indication of expected growth in consumption in Southern African countries.

Table 27: Electricity consumption forecasts by country in the Southern African region Country 2010 2015 2020 2025 2030

Botswana Energy requirements [GWh] 4202 5298 6848 7336 8655

Peak Demand [MW] 737 928 1183 1272 1470

Mozambique* Energy requirements [GWh] 3758 4898 5966 7262 8374

Peak Demand [MW] 557 714 876 1240 1475

Namibia Energy requirements [GWh] 2992 3353 3940 4629 5239

Peak Demand [MW] 509 651 779 933 1074

South Africa Energy requirements [GWh] 259685 300425 355694 404358 454357

Peak Demand [MW] 38885 44865 52719 60150 67809 *Excludes consumption of MOZAL Aluminium Smelter, which is accounted for in the Souh Africa demand


63

The forecasts shown in Table 27 above for Botswana, Mozambique and Namibia are based on the SAPP Power Pool Forecasts17 (which extend to 2025) and were extrapolated to 2030. The forecast for South Africa was taken from the Integrated Resource plan 2010-2030.18 The consumption data for each country as shown in Table 27 was used as the inputs in the model for the electricity demand of the Southern African region.

Figure 20: Estimated electricity system demand in the Southern African region up to 2030

2.3.7 POWER GENERATION EXPANSION POSSIBILITIES IN THE SOUTHERN AFRICAN REGION - SUMMARY

The main medium-term generation expansion options in the region are coal based thermal power plants, gas/oil thermal power plants and large scale hydro. In the slightly longer term South Africa is also considering a nuclear build program. A certain amount of electricity from renewables (wind and solar) is under consideration in all four countries. Large coal reserves are available in all four countries considered in this study, with South Africa being the most advanced in its exploitation both for export, electricity generation and coal to liquids processes. The three other countries are currently expanding the exploitation of their coal resources with plans of using it for power generation. South Africa has limited natural gas supplies in off-shore oil/gas fields. The dwindling gas reserves are all already allocated to the PetroSA gas to liquids plant, not leaving any for large scale gas-powered generation. Although there is currently talk of exploitation of shale gas and coal-bed methane, in the medium-term any large scale power generation from gas would either have to be from LNG or gas piped down from Mozambique or Namibia. Both Namibia and Mozambique have some natural gas reserves that they are considering exploiting for large-scale power generation. Botswana is considering using coal bed methane for power generation.

17

Nexant 2007, SAPP Regional Generation and Transmission Expansion Plan Study, SAPP Co-ordination Centre, Gabarone. 18

DOE 2011, Integrated Resource Plan for Electricity 2010-2030 (In promulgation).

0

100

200

300

400

500

600

TWh Namibia

Mozambique

Botswana

South Africa


64

There is large scale hydro potential in Mozambique and Namibia. In the longer term, increased regional cooperation could see the exploitation of the vast hydro resources found further north in the region, namely in Zambia, Angola and the DRC. A summary of hydro options are given in Table 28. There is quite significant biomass potential in Mozambique, but currently there are no real plans of exploitation. The “Working for Water” and “Working for Energy” programs in South Africa show promise for some exploitation of the biomass potential in South Africa, but the potential is limited. Namibia and Botswana also have very limited biomass potential for power generation. Wind resources are good in South Africa and Namibia, and all four countries have excellent solar resources.

Table 28: Hydro options in the Southern African region Country Plant name Earliest year

(optimistically) Capacity [MW]

Capacity factor

Mozambique Lurio 2012 183 35.1%

Quedas & Ocua 2012 179 41.5%

Mphanda Nkuwa 2015 1300 79.6%

HCB North Bank 2015 850 38.1%

Namibia Baynes 2013 360 54.7%

2.3.1. CO2 EMISSION SOURCES FROM POWER GENERATION IN THE SOUTHERN AFRICAN REGION – SUMMARY

The largest sources of CO2 emissions in the region come from the coal power stations in South Africa, listed in Table 29 below. CO2 emission estimates in 2010 according to DOE IRP 2011 for South Africa are around 237 Mton. Estimates for the emissions in the rest of the region are summarized in Table 30.

Table 29: South Africa coal plant CO2 emissions for 2006 Name of Station Total

Capacity19

Output 2006

20

Efficiency11

CO2 Emissions

21

Expected decommissioning

10

MW GWh % Mt 2006

Eskom demothballed

Camden 1 520 1 769 27.9% 2.2 2025

Grootvlei 372 - 27.0% - >2030

Komati 202 - 25.5% - >2030

Eskom Coal

Arnot 2 280 12 683 32.3% 13.6 2023

Duvha 3 450 25 246 34.7% 25.2 >2030

Hendrina 1 870 11 718 31.6% 12.8 2022

Kendal 3 840 27 934 35.0% 27.7 >2030

Kriel 2 850 19 209 35.9% 18.5 2028

19

DOE 2011, Integrated Resource Plan for Electricity 2010-2030. 20

NERSA 2007, NIRP3 Stage 3 Report, NERSA. 21

Estimated using 96.25 t/TJ (LTMS 2007).


65

Lethabo 3 558 24 868 35.3% 24.4 >2030

Majuba Dry 1 851 8 570 35.0% 8.5 >2030

Majuba Wet 1 992 9 222 37.6% 8.5 >2030

Matimba 3 690 28 212 35.4% 27.6 >2030

Matla 3 450 25 388 35.2% 25.0 2029-30

Tutuka 3 510 18 374 37.5% 17.0 >2030

Non-Eskom Coal

Kelvin "A" 50 231 24.0% 0.3

Kelvin "B" 153 942 24.9% 1.3

Pretoria West 75 130 23.5% 0.2

Rooiwal 153 816 24.9% 1.1

Sasol SSF 520 4 513 25.4% 6.1

Table 30: Power sector CO2 emissions for Botswana, Mozambique and Namibia Name of station Total

capacity Output

est. Efficiency

CO2

emissions Expected

decommissioning

MW GWh % Mt/yr

Botswana: Morupule (coal) 120 788 30% 0.9

Mozambique: (diesel) 90 383 30% 0.48

Namibia: Van Eck (coal) 120 78 30% 0.09

Namibia: Paratus (diesel) 24 105 30% 0.003

2.4. COUNTRY DETAILS – SOUTHERN AFRICAN REGION

2.4.1. SOUTH AFRICA

The Republic of South Africa is located at the southern-most tip of Africa with a total land mass of 1,219,090 km2 and a coastline of 2,798 km on the Atlantic and Indian Oceans. Namibia, Botswana, and Zimbabwe lie to the north while Mozambique and Swaziland lie to the northeast. Additionally, Lesotho is surrounded by South Africa in the mid-east part of the country. South Africa’s population is estimated at nearly 50 million with an estimated GDP per capita (PPP) of $10,70022. Further key indicators are shown in the table below.23

22

CIA World Factbook, web 22 February 2011 and Wikipedia, web 22 February 2011. 23 Source: IEA.


66

Table 31: Key indicators for South Africa in 2008 (Source: IEA)

Key indicators Compound indicators

Population (million) 48.69

TPES/population (toe/capita) 2.76




Net imports (Mtoe) -17.44 CO2/TPES (t CO2/toe) 2.51




* Gross production + imports - exports - losses

** CO2 Emissions from fuel combustion only. Emissions are calculated using IEA's energy balances and the Revised 1996 IPCC Guidelines.

Table 32 and Table 33 show South Africa’s existing generation plants as of 2008 that are specified in the model. Eskom, the national power utility, generates the bulk of the country’s electricity from coal. Eskom’s total installed capacity is 44,177 MW which includes a otal installed generation capacity of 44,114 MW plus an additional 61 MW from Colley Wobbles, First Falls, Ncora and Sexcond Falls hydro power stations that are operated by the Distribution Division24 (Eskom, October 2010). The Generation Division has 13 coal-fired power stations with an installed capacity of 37,755 MW. Their total net output excluding the power consumed by the auxiliaries and generators is 34,658 MW. Africa’s only nuclear power station, Koeberg, located in Cape Town, is a baseload station with a capacity of 1,800 MW. The private coal-fired power stations comprise two chemicals and synthetic fuels based plants for SASOL and the Kelvin power station owned by City Power, while the bagasse private generation facility is mostly owned by the Tongaat-Hulett sugar group.

24

NERSA 2010, Electricity Supply Statistics 2006.


67

Table 32: Input parameters for existing coal plants in South Africa Name of station Heat

rate Output

2006 No of units

Max unit capacity

Total cap

Planned outage rate

Forced outage rate

Availability Variable costs

Fixed Costs

Year online

Btu/kWh GWh MW MW R/MWh R/kW

Eskom demothballed

Camden 12 214 1 769 8 190 1 520 7.96% 16.99% 76.40% 7.00 127 1986

Grootvlei 12 638 - 6 62 372 7.96% 16.99% 76.40% 4.39 204 1988

Komati 13 382 - 5 40 202 7.96% 16.99% 76.40% 2.65 187 1989

Eskom Coal

Arnot 10 555 12 683 6 380 2 280 8.95% 7.15% 84.54% 10.00 314 1975

Duvha 9 831 25 246 6 575 3 450 8.98% 4.74% 86.71% 3.00 169 1980

Hendrina 10 792 11 718 10 187 1 870 7.37% 9.15% 84.15% 8.00 351 1970

Kendal 9 755 27 934 6 640 3 840 5.89% 3.20% 91.10% 4.00 122 1988

Kriel 9 510 19 209 6 475 2 850 6.98% 9.38% 84.29% 8.00 298 1976

Lethabo 9 671 24 868 6 593 3 558 8.05% 6.81% 85.69% 8.00 129 1985

Majuba Dry 9 763 8 570 3 617 1 851 5.78% 5.78% 88.77% 7.00 134 1996

Majuba Wet 9 074 9 222 3 664 1 992 6.78% 5.83% 87.79% 13.00 90 1996

Matimba 9 648 28 212 6 615 3 690 7.80% 5.49% 87.14% 6.00 200 1987

Matla 9 692 25 388 6 575 3 450 5.46% 6.73% 88.18% 10.00 188 1979

Tutuka 9 100 18 374 6 585 3 510 10.09% 4.65% 85.73% 7.00 127 1985

Non-Eskom Coal

Kelvin "A" 14 239 231 2 25 50 10.09% 9.38% 81.48% 18.00 371 1982

Kelvin "B" 13 688 942 3 51 153 10.09% 9.38% 81.48% 18.00 302 1982

Pretoria West 14 545 130 3 25 75 10.09% 9.38% 81.48% 18.00 697 1982

Rooiwal 13 688 816 3 51 153 10.09% 9.38% 81.48% 17.00 241 1982

Sasol SSF 13 419 4 513 10 52 520 8.98% 7.15% 84.51% 14.00 138 1982

Existing coal Large (>350MW) 35.1% 199 706 54 564 30 471 7.54% 5.84% 87.06% 7.21 175


68

Existing coal Small (<350MW) 28.4% 20 118 50 98 4,915 8.03% 12.30% 80.65% 8.68 242

Table 33: Input parameters for existing plants other than coal in South Africa Name of station Heat

rate Output

2006 No of units

Max unit capacity

Total cap

Planned outage rate

Forced outage rate

Availability Variable costs

Fixed costs

Year online

Btu/kWh GWh MW MW R/MWh R/kW

Acacia 12 186 36 3 57 171 3.48% 4.55% 6% 101.00 67 1976

Atlantis 10 432 - 9 147 1 323 7.36% 5.25% 6% 268.00 65 2007

Mossel Bay 10 177 - 5 147 735 7.36% 5.25% 6% 268.00 67 2007

Port Rex 12 186 22 3 57 171 3.26% 4.35% 6% 106.00 71 1976

Total liquid fuels 20 120 2 400 5.14% 6% 244.56 66.18

Mini Hydros - 1 65 65 3.91% 8.50% 13.78% 114 1976

Gariep 1 325 4 90 360 4.85% 4.99% 12.7% 115 1971

Vanderkloof 1 409 2 120 240 3.91% 8.50% 19% 115 1977

Pumped storage 3 096 9 176 1 580 5.13% 6.80% 19.4% 3.37 59.42

Drakensberg 2 033 4 250 1000 5.51% 7.80% 18.8% 3.00 60 1981

Palmiet 900 2 200 400 4.00% 3.86% 24.5% 4.00 64 1988

Steenbras 163 3 60 180 5.51% 7.80% 11.4% 4.00 46 1971

Total Hydro 2 734 7 95 665 15.08% 114.9

PWR nuclear 10 663 13 668 2 900 1 800 11.23% 8.71% 81.0% 10.00 416 1984


69

The following table shows the committed electricity plant build programme according to the latest DOE 2011 IRP document. This committed plan is fixed in all the scenarios modelled for South Africa.

Table 34: Committed build plan from DOE IRP201025

Committed build R

TS

Ca

pa

cit

ry

Me

du

pi

(Co

al)

Ku

sil

e (

Co

al)

Ing

ula

(P

S)

DO

E O

CG

T I

PP

Co

ge

ne

rati

on

Win

d

CS

P

La

nd

fill,

hy

dro

Se

re (

Win

d)

De

co

mm

.

MW MW MW MW MW MW MW MW MW MW MW

2010 380 0 0 0 0 260 0 0 0 0 0 2011 679 0 0 0 0 130 0 0 0 0 0 2012 303 0 0 0 0 0 300 0 100 100 0 2013 101 722 0 333 1020 0 400 0 25 0 0 2014 0 722 0 999 0 0 0 100 0 0 0 2015 0 1 444 0 0 0 0 0 100 0 0 -180 2016 0 722 0 0 0 0 0 0 0 0 -90 2017 0 722 1 446 0 0 0 0 0 0 0 0 2018 0 0 723 0 0 0 0 0 0 0 0 2019 0 0 1 446 0 0 0 0 0 0 0 0 2020 0 0 723 0 0 0 0 0 0 0 0 2021 0 0 0 0 0 0 0 0 0 0 -75 2022 0 0 0 0 0 0 0 0 0 0 -1 870 2023 0 0 0 0 0 0 0 0 0 0 -2 280 2024 0 0 0 0 0 0 0 0 0 0 -909 2025 0 0 0 0 0 0 0 0 0 0 -1 520 2026 0 0 0 0 0 0 0 0 0 0 0 2027 0 0 0 0 0 0 0 0 0 0 0 2028 0 0 0 0 0 0 0 0 0 0 -2 850 2029 0 0 0 0 0 0 0 0 0 0 -1 128 2030 0 0 0 0 0 0 0 0 0 0 0

Total 1 463 4 332 4 338 1 332 1 020 390 700 200 125 100 -10 902

Eskom’s Integrated Report 2010 states that South Africa’s peak demand in 2010 was 35,850 MW from a total number of nearly 4.5 million customers with reported sales of 205,364 GWh domestically and 13,227 GWh internationally. This represents a sales growth of 1.7% while foreign imports was 10,047 MW.26 The report also states that the adequacy of electricity supply in 2012-13 depends on the efficacy of DSM initiatives. Should these initiatives not be sufficient, high load-factor supply-side options such as co-generation may be required. In the longer term, the report states that 20GW of additional generation capacity will be required before 2020 and up to 40GW before 2030. Independent Power Producers (IPP’s) are anticipated to provide 14GW by 2017. The report also shares plans for transmission network and a summary of assets to be installed over the next 10 years is shown in Table 35 below.

25

NERSA 2010, Electricity Supply Statistics 2006. 26

Eskom 2010, Integrated Report 2010.


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Table 35: Major transmission assets expected to be installed27 TDP new asset Total

HVDC lines (km) 1 700

765kv lines (km) 6 770

400kv lines (km) 8 355

275kv lines (km) 831

Transformers 250MVA+ 103

Transformers <250MVA 29

Total installed MVA 840

Capacitors 19

Total installed MVAr 2 366

Reactors 56

Total installed MVAr 14 600

A map showing the transmission grid with possible expansion relative to the power stations in South Africa is shown in Figure 21 below.

Figure 21: South African Power Network with interconnections to neighbouring countries28

27

Eskom Integrated Report 2010. Johannesburg: Eskom, 2010. 28

Reporting on Progress United Nations Global Compact. 21 June 2010. http://www.eskom.co.za/annreport10/fact_sheets/eskom_unbgi.htm (accessed March 30, 2011).


71

In terms of climate change considerations, South Africa is regarded as a Non-Annex 1 country in the United Nations Framework Convention on Climate Change. South Africa acceded to the Kyoto Protocol on 31st July 2002 and ratified it on 16th February 2005.29 As a Non-Annex 1 Country South Africa did not have any commitments towards the Kyoto Protocol, however, as part of the Copenhagen Accord of 2009 South Africa has stated that it “will take nationally appropriate mitigation action to enable a 34% deviation below Business As Usual emissions growth trajectory by 2020 and a 42% deviation below the business as usual trajectory by 2025”.30 This represents a target of 275Mt from the power sector by 2025.

2.4.2. NAMIBIA

Namibia lies on the southwest coast of Africa bordered by the South Atlantic Ocean to the west, Angola to the north, Zambia to the northeast in an area called the Caprivi Strip, Botswana in the east, and South Africa along the south and southeast. Namibia is roughly 824,300 km2 with a population of about 2.1 million people and is considered one of the most sparsely populated countries in the world. It is also the most arid country in sub-Saharan Africa with an average rainfall from 10 mm at the coast to 600 mm in the northeast. Key indicators for Namibia are shown in Table 36 below.

Table 36: Key Indicators for Namibia in 2000

Key indicators

Compound indicators











29 UNFCCC. Status of Ratification of the Kyoto Protocol. n.d.

http://unfccc.int/kyoto_protocol/status_of_ratification/items/2613.php (accessed March 30, 2011). 30

Wills, A. (2010). Nationally appropriate mitigation actions of South Africa. Retrieved March 30, 2011, from UNFCCC Copenhagen Accord: http://unfccc.int/files/meetings/cop_15/copenhagen_accord/application/pdf/southafricacphaccord_app2.pdf


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The primary sectors of the Namibian economy are mining, agriculture and fisheries. Mining accounts for 8% of the GDP, but more than 50% of the country’s export earnings.31 Between 2001 and 2009, GDP grew on average at 4% per annum.32 Namibia is a primary source of gem-quality diamonds, the fourth largest exporter of nonfuel minerals in Africa, the world’s fifth-largest producer of uranium, and a major producer of lead, zinc, tin, silver and tungsten.33 The Aranos Basin has coal reserves amounting to around 350 million tons at a depth between 200-300 metres, although the feasibility of exploiting this remains unknown (SADC, 2007). Namibia is a net importer of electricity and has limited generation capacity. The national power utility is Nampower, which has an installed supply capacity of 993MW. The current generation facilities are shown in Table 37 below.

31

CIA World Factbook, 2011. 32

De Coninck, H., Mikunda, T., Cuamba, B., Schultz, R., & Zhou, P. (2010). CCS in Southern Africa. Energy Research Centre of the Netherlands. 33

CIA World Factbook, 2011.


73

Table 37: Parameters for installed generation capacity of thermal power plants in Namibia34 Name of station Unit

capacity No of units

Plant capacity

Heat rate (max cap)

Fuel Variable O&M

Fixed O&M

Planned outage

Forced outage

Availability

MW MW kJ/kWh USD/MWh USD/kW

Van Eck 27 4 120 12,000 Coal 7.4 56.67 7.2% 5.17% 88%

Paratus 6 4 24 12,000 Distillate 5.35 4.86 2.03% 2.11% 95.9%

Table 38: Parameters for installed generation capacity of thermal power plants in Namibia Name of station Unit

capacity # of

units Plant

capacity Average

generation Dry year

generation Variable

O&M Fixed O&M

Planned outage

Forced outage

Average CF Dry Year CF

MW MW GWh GWh USD/MWh USD/kW

Ruacana 80 3 240 1,395 921 1.51 8.72 5% 2% 66.4% 43.81%

34

Nexant 2007, SAPP Regional Generation and Transmission Expansion Plan Study, SAPP Co-ordination Centre, Gabarone.


74

These facilities generate less than half of the required supply, and so Namibia imports electricity from South Africa and other countries in the region. Table 39 illustrates the import dependency by showing the origin of imports by utility and the local generation.

Table 39: Electricity generated, imported and exported in Namibia June2008-June200935 Local generation GWh Imports GWh

ZESA 648

Ruacana 1395 ESKOM 654

EDM 24

Van Eck 78 ZESCO 29

Total Imports 1355

Paratus 3 Exports GWh

BPC 137

Total local generated 1490 ZESCO 7

Total exported 144

In terms of future supply, Nampower’s generation business unit has reported the following potential and committed projects:

1. Short term emergency generation Anixas Initially planned as a 50MW plant, however joint venture partner withdrew due to the financial crisis. Government has invited bids for diesel generation of 20-30MW on this site.

2. Hydro power station Ruacana Unit 4 A 104MVA generator and hydro turbine project has commenced and 90MW is expected to be online by March 2012.

3. Coal power station, Walvis Bay Nampower’s intention is to solicit IPPs to develop this project which is still in feasibility stages.

4. Orange River hydros This is a joint development by Nampower and Clackson Power on The Lower Orange River Hydro Power Scheme (LOHEPS). The potential capacity is 80-120MW obtainable from 10 individual sites along the Lower Orange River below the Augrabies falls.

5. Slop project This is a project that is intended to use recycled waste oils, fuels and slops recovered mainly from compulsory discharges in the shipping industry to generate approximately 80MW of electricity.

6. Hwange Power Station refurbishment This is a contract between Nampower and ZESA (Zimbabwe) aimed at rehabilitation of the Zimbabwean coal plant. ZESA has reliably delivered 150MW to Namibia since 2008.

7. Baynes hydro project This is a project looking at developing hydro electric potential on the Cunene River Basin between Angola and Namibia. According to the 2009 Nampower Annual Report the project was in its feasibility stage.

8. Kudu Gas project This project is intended to make use of the Kudu Gas Field which is located roughly 170 km offshore of the southern Namibian coastline. A proposed 800MW Combined Cycle Gas Turbine (CCGT) was initially proposed with Eskom of South Africa being the anchor customer. However, talks with Eskom stalled in 2007 and the alternative of Compressed Natural Gas (CNG) shipment is being explored.

35

Nampower. (2009). Annual Report 2009. Windhoek: Nampower.


75

The Electricity Control Board (ECB) of Namibia’s annual report also indicates licences that have been issued to Independent Power Producers (IPP). However, according to the ECB Annual Report, no Power Purchase Agreements (PPA) with any IPPs had yet been signed. The transmission system in Namibia can be seen in Figure 22 below. Projects embarked on by Nampower include:36

1. Caprivi link interconnector HVDC link between Zambia and Namibia that will provide an alternative route of for trading in the region.

2. West-coast development Largely supporting mine development and growth along this corridor.

3. Ohorongo Cement Plant Supply of a 132kV line to the cement plant.

4. Upgrade of Van Eck Transmission Station Larger capacity transformers are being installed at this substation.

5. Ondjiva Cross-Border Supply This is an upgrade from 33kV to 132kV supply point to Angola.

6. Ruby Substation Replacement of a substation that supplies the Rooikop Airport and Namwater pumping in Walvis Bay.

7. Zizabona Interconnection Emanating from an Inter-utility MOU between Zimbabwe, Zambia, Namibia and Botswana utilities and is a SAPP endorsed project aimed at enhancing trade between northern and southern parts of SAPP western grid.

8. Demand side management Resulted in the distribution of 900,000 CFLs and the implementation of time of use tariffs, demand management programme and a load-shedding schedule.

36

Nampower. (2009). Annual Report 2009. Windhoek: Nampower.


76

Figure 22: Namibian Transmission System with future build plans

In terms of climate change frameworks, Namibia is regarded as a Non-Annex 1 country in the United Nations Framework Convention on Climate Change. Namibia acceded to the Kyoto Protocol on 4th September 2003 and ratified it on 16th February 2005.37 In 2000, the primary sources of greenhouse emissions for Namibia were the agriculture (6.7 Mt CO2eq) and energy (2.2 Mt CO2eq) sectors and 0.239 Mt CO2eq were attributable to energy


http://unfccc.int/kyoto_protocol/status_of_ratification/items/2613.php (accessed March 30, 2011).


77

industries.38 0.0739 Mt of CO2eq was attributable directly to Nampower’s use of fossil fuels. The country was a net carbon sink, sequestering a total carbon dioxide equivalent of about 1.4 Mt per annum.39 Various projects underway could change the net sink status such as the harvesting of 80,000 tonnes of biomass (invader species) for wood gasification plants, coal-fuel replacement for cement production and export of wood pellets, and the commissioning of a cement factory with an estimated annual coal consumption of 120,000 tonnes 40.

2.4.3. MOZAMBIQUE

Mozambique is located in the southeast part of Southern Africa and has a total land area of 799,380 km2 and a coastline of 2,470 km. The population is estimated at a little over 22 million inhabitants (2010). In 2008, 37% of the population lived in urban areas. The GDP growth rate was estimated 6.8% in 2008, 6.3% in 2009 and 8.3% in 201041. Selected key indicators are shown in the table below.

Table 40: Key Indicators for Mozambique

Key Indicators

Compound Indicators




Energy production (Mtoe) 11.46 Electricity Cconsumption / population (kWh/capita) 474

Net imports (Mtoe) -2.07 CO2/TPES (t CO2/toe) 0.21


Electricity Cconsumption* (TWh) 10.33 CO2/GDP (kg CO2/2000 USD) 0.24




The total installed generation capacity of Mozambique is around 2,185 MW with 2,075MW sourced from the existing Cahora Bassa Hydropower Scheme (operated by Hydroelectrica De Cahora BassaHCB). The SADC Energy Statistical Yearbook 2007 gives the proportions by which the power from Cahora Bassa is distributed regionally. Of the 2,075MW, 400MW are allocated to Mozambique, 200MW to Zimbabwe, 50MW to Botswana and the remainder allocated to South Africa. However, South Africa supplies 900MW to the Mozal Aluminium smelter in Mozambique.42

38

Hartz, C., & Smith, C. (2008). Namibia’s Greenhouse Gas Inventory for Year 2000. Windhoek: Ministry of Environment and Tourism Namibia. 39

Hartz, C., & Smith, C. (2008). Namibia’s Greenhouse Gas Inventory for Year 2000. Windhoek: Ministry of Environment and Tourism Namibia. 40


CIA World Factbook, 2011 42

SADC. (2007). SADC Energy Yearbook 2007. Gabarone: SADC.


78

Mozambique’s national maximum electricity demand in 2009 was 481MW at a load factor of 64%, a 15.6% increase over 2008 maximum demand.43 The total amount of electricity generated in 2009 in Mozambique for distribution was 31,93GWh (comprising 87% from the Cahora Bassa Hydropower scheme, 12% generated by Electricidade De Moçambique (EDM), the National Utility, and 1% imported from neighbouring countries and excluding export from HCB). Of the electricity consumed in 2009 in Mozambique, 54% was used in the southern region, 18% in the Central region, 16% was exported, 9% was consumed by the northern region and 3% was sold to special customers.44 Parameters for existing power plants in Mozambique are given in Table 41 and Table 42. Future planned power projects in Mozambique include45:

Mphande Nkuwa Hydroelectric power project which is Situated 60km downstream from Cahora Bassa with a potential for 2400MW installed capacity of which phase 1 (1,500MW) is expected to be operational by 2014

Moatize Coal Power station, a 2,400MW Capacity plant expected by 2015

Benga Coal Power station, a 2,000MW plant of which the first phase is planned for completion in 2015

Moamba Gas power plant with a capacity of 750MW and commissioning date of 2013

The 1,500km Tete-Maputo Backbone 400kV transmission line. A diagram illustrating the extent of the transmission network Mozambique with links to neighbouring countries and power stations can be seen in Figure 23Error! Reference source not found. below. The transmission lines linking Mozambique (Songo) and South Africa, and Mozambique and Zimbabwe are High Voltage Direct Current (HVDC) lines. Also shown in the figure are the natural gas fields of Pande and Temane and pipelines of this gas to Sasol in South Africa.

43

EDM. (2009). Annual Statistical Report 2009. Maputo: EDM. 44

EDM. (2009). Annual Statistical Report 2009. Maputo: EDM. 45

SADC. (2007). SADC Energy Yearbook 2007. Gabarone: SADC, dates updated using ECN 2010, CCS in Southern Africa, Energy Research Centre of the Netherlands, July 2010.


79

Table 41: Parameters for installed generation capacity of thermal power plants in Mozambique46 Name of station Unit

capacity No of units

Plant capacity

Heat rate (max cap)

Fuel Variable O&M

Fixed O&M

Planned outage

Forced outage

Availability

MW MW kJ/kWh USD/MWh USD/kW

Mozambique

Maputo 26 2 52 12 142 Distillate 3 0.8 15% 5.77% 80.1%

Beira + other 38 38 12 142 Distillate 3 0.8 15% 5.77% 80.1%

Table 42: Parameters for installed generation capacity of hydro power plants in Mozambique Name of station Unit

capacity # of

units Plant

capacity Average

generation Dry year

generation Variable

O&M Fixed O&M

Planned outage

Forced outage

Average CF Dry Year CF

MW MW GWh GWh USD/MWh USD/kW

Cahora Bassa 415 5 2,075 15 300 12 000 1.51 8.72 5% 2% 84.2% 66.02%

Other Hydros 10.4 4.5 47 304 107 1.51 8.72 5% 2% 73.84% 25.99%

Chicamba 17 1 17 46 10 1.51 8.72 5% 2% 15.4% 6.72%

Corumana 6 2 12 21 11 1.51 8.72 5% 2% 20.4% 10.46%

Mavuzi 12 1.5 18 237 86 1.51 8.72 5% 2% 75.2% 54.54%

46

Nexant 2007, SAPP Regional Generation and Transmission Expansion Plan Study, SAPP Co-ordination Centre, Gabarone.


81

Figure 23: Mozambiquan transmission network47

47

http://www.geni.org/globalenergy/library/national_energy_grid/mozambique/mozambiquenationalelectricitygrid.shtml (accessed March 30, 2011)

http://www.geni.org/globalenergy/library/national_energy_grid/mozambique/mozambiquenationalelectricitygrid.shtml

http://www.geni.org/globalenergy/library/national_energy_grid/mozambique/mozambiquenationalelectricitygrid.shtml


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In terms of climate change considerations, Mozambique is regarded as a Non-Annex 1 country in the United Nations Framework Convention on Climate Change. Mozambique acceded to the Kyoto Protocol on 18th January 2005 and ratified it on 18th April 2005.48 In 1994, the primary sources of greenhouse gas emissions for Mozambique were agriculture (0.891 Mt CO2eq) and energy (0.359 Mt CO2eq) sectors of which 0.0645 Mt CO2eq were attributable to energy industries49. The Mozambican First National Communication to the UNFCCC reported direct CO2 emissions of 9.265 Mt per annum, with 2004 as the reference year and the energy sector accounting for approximately 16.5% of these emissions.50

2.4.4. BOTSWANA

Botswana is a landlocked country centred between Zambia, Zimbabwe, South Africa and Namibia. At no point is the country closer than 500km to either the Atlantic or Indian Oceans.51 The total area within its national borders is 581,730 km2. The population of Botswana and other key indicators are shown in the table below.

Table 43: Key Indicators for Botswana

Key indicators

Compound indicators




Energy production (Mtoe) 1.00 Electricity Consumption / population (kWh/capita) 1516







Nearly two-thirds of the country is semi-arid with between 70-80% (centre, west and south-west) covered by the Kalahari Desert. The north-west contains the large delta known as the Okavango with the water emanating from Angola along the Okanvango River and travelling through the Caprivi Strip of Namibia. Nearly all areas of the country receive less than 500 mm of rainfall per year.52 Botswana has maintained one of the world’s highest economic growth rates since its independence from Britain in 1966, albeit with declines between the years 2007-2009, and has thus transformed



UNFCCC, GHG Emissions Summary for Mozambique 50


FAO 2005 52

SADC Energy Statistical Yearbook, 2007


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itself from one of the poorest countries in the world to a middle-income country53. The GDP (purchasing power parity) of Botswana in 2010 was estimated at 26.56 billion USD with a GDP per capita of 13,100 USD. Diamond mining currently accounts for more than one-third of its GDP, 70-80% of its export earnings, and about half of the government’s revenues. Tourism, financial services, subsistence farming, and cattle raising are other key sectors of the economy. Table 44 shows the input parameters for existing thermal power plants of Botswana used in the model.

Table 44: Parameters for installed generation capacity of thermal power plants in Botswana54 Name of station Plant

capacity Heat rate (max cap)

Fuel Variable O&M

Fixed O&M

Planned outage

Forced outage

Availability

MW kJ/kWh USD/MWh USD/kW

Morupule 120 12,000 Coal 7.4 56.67 7.20% 5.17% 88%

Botswana imported 83% of its electricity from its neighbouring countries (South Africa 60%, Mozambique 19% and Namibia 4%55) in 2009. The remainder (17%) is from on coal-fired power at the Morupule Power Station (Morupule A) which has a capacity of 120 MW. The current system maximum demand is 503 MW with final energy consumption 2,916.9 GWh in 2009 dominated by the mining sector (39%) followed by the domestic (26%), commercial (25%), and government (10%) sectors.56 Future electricity plant build plans for Botswana include:57

The Morupule B Power Station (600 MW) is expected to come on-line in 2013. The Botswana Power Corporation (BPC) plans to add another 600 MW by 2016.

IPPs are planning and developing two further coal-fired power stations, i.e. a 1,200 MW coal-fired power plant at the Mmamabula coalfield and a 1,000 MW power plant at the Mmamantswe coalfield.

Additionally, a 200 MW power station based on coal bed methane is expected by 2020.

A total of 160 MW of diesel generators are also expected to be installed by the end of 2010.

CIC Energy are planning to build a coal mine and power station at Mmamabula. The company has been considering a ‘capture ready’ power station thus allowing for CO2 capture to be available when the regulatory and economic factors are favorable.58

The transmission network in Botswana is shown in Figure 24. The figure also shows proposed lines and interconnections with other neighbouring countries. Various transmission line projects are underway of which the following are most recent:59

53

CIA World Factbook, 2011. 54

Nexant 2007, SAPP Regional Generation and Transmission Expansion Plan Study, SAPP Co-ordination Centre, Gabarone. 55

BPC. (2009). Annual Report 2009. Gabarone: BPC. 56

BPC. (2009). Annual Report 2009. Gabarone: BPC. 57

de Coninck, H., Mikunda, T., Cuamba, B., Schultz, R., & Zhou, P. (2010). CCS in Southern Africa. Energy Research Centre of the Netherlands. 58

Based on a 2007 study prepared by Andrew Minchester of the Energy Conversion Group and cited in the CCS Africa factsheet on Botswana. 59

BPC. (2009). Annual Report 2009. Gabarone: BPC.


84

The new 220 kV line from Phokoje to Hydromet; the associated 220/66/11 kV Hydromet substation begun in December 2008 and March 2009 respectively, to provide firm and secure supply to Tati Nickel Mine and their operations at Phoenix.

A 132/11 kV 40 MVA substation in Phakalane, including its 132 kV supply line from Segoditshane 220/132 kV substation were commissioned in March 2009, thus firming supplies to the Phakalane and Mochudi residential areas.

A major highlight on the Botswana power grid development is the commencement of the 400 kV transmission lines and 400/220 kV 630 MVA substation development projects for transportation of power from the planned Morupule B 600 MW power station.

Four large projects to increase capacity to one of the major customers and to connect two new customers were suspended on customers’ requests due to the global economic financial crisis and resulting reduced mineral prices, thus affecting viability of these projects.

Figure 24: Botswana Transmission Network60

In terms of climate change mitigation, Botswana is regarded as a Non-Annex 1 country in the United Nations Framework Convention on Climate Change and the country acceded to the Kyoto Protocol on 8th August 2003 and ratified it on 16th February 2005.61

60

BPC. (2009). Annual Report 2009. Gabarone: BPC.


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Based on 1994 data, the Botswana Initial National Communication of 2001 on their CO2 emissions were 9.315 Mt dominated by agriculture (55%), then power generation (19%), mining and industry (11%), transport (9%), households (4%), and government (1%).62 Botswana is in the process of updating its GHG inventory based on 2003 data63.



UNFCCC, GHG Emissions Summary for Botswana 63

De Coninck, H., Mikunda, T., Cuamba, B., Schultz, R., & Zhou, P. (2010). CCS in Southern Africa. Energy Research Centre of the Netherlands.

CHAPTER 3 Storage capacity

86

CHAPTER 3 STORAGE CAPACITY

3.1.1. IDENTIFICATION METHOD

In order to investigate the potential of CCS in the Balkan and Southern African regions, the storage potential for CO2 must be known. Data collection and analysis has been carried out to estimate the storage potential in individual locations for both regions. The storage capacity identification carried out for this study has been based on previous studies documenting the CCS potential and/or the geological reservoir characterization in the selected regions. For South Africa the “Atlas on geological storage of carbon dioxide in South Africa” (2010) and its associated technical report (Viljoen et al., 2010) with the extended data forming the main documents were used. This information has been completed with data from academic theses, papers, presentations and industrial information available through the internet. For the other African countries the latter sources form the basis for capacity assessment. For the Balkan region the EU GeoCapacity project (FP-6 report 2006-2009) served as the main source of data. Although much effort has already been made to assess geological storage capacity, much basic data is still missing and major exploration is required in order to reduce uncertainties. The defined capacities used in the model are to be considered as theoretical capacities calculated based on estimated volumes of reservoir rock. The real storage capacity can only be estimated once sufficient data is available on the size of individual structures, the presence of sealing strata, the porosity and permeability of the reservoirs and the storage efficiency. This level of detail could not be specified for the selected regions. The results of the data collection and analysis are summarized in a reservoir matrix for each region, Tables 124 and 125 in Annex A. These tables contain the potential storage options, give the known reservoir characteristics, outline the uncertainties and exploration needs, specify the bottlenecks, indicate the time of availability for a certain option, and report the used references. These tables can be updated in the future when more exploration data becomes available. The options are classified in these tables using a color code. Red signifies “not an option” for storage, orange for “might be possible, but requires fundamental exploration before capacity can be confirmed”, yellow means “possible, but major exploration required” and green “possible with limited exploration efforts required”. The colors do not refer to economic feasibility. The reservoir options in green and yellow have been considered explicitly as possible storage options for the modeling exercise, where the non-economic options have been excluded once cost considerations were taken into account. The reservoir matrices and a short summary per country are given in Annex A. Ageneral summary of the results is provided in this chapter, together with some implications and recommendations regarding the suitability of storage reservoirs.

3.1.2. RESULTS


87

Lack of data is a general issue in the different regions that hinders quantitative estimates of storage capacity. Most of the information from previous studies relates to industrial applications, such as the mining of natural resources, petroleum fields and the associated exploration efforts. CCS-specific research in these areas has been very minor. Nevertheless, the industrial development of geological resources, such as oil and gas mining, offers information to aid potential storage reservoir identification, provides insight as to the potential symbiosis between CO2 storage and oil or gas recovery (EOR – Enhanced Oil Recovery; EGR – Enhanced gas recovery; ECBM – Enhanced coalbed methane) and potential sites equipped with the infrastructure that can store CO2 (depleted fields). The different options can be categorized within the following storage reservoir types:

1) The large capacity storage options (Gton range) are to be found in saline aquifers. The aquifers in sedimentary basins are not sufficiently characterized at present. In all investigated countries there is a lack of data on reliable quantitative estimates of such storage capacity. Major uncertainties such as evidence on containment (details on caprocks, seals, geometry and faults), injectivity, and capacity of individual structures etc. remain, and require an intensive (and hence expensive) pre-injection exploration program. Further, development of a storage site would be more expensive in areas where no drilling activity related to commercial activities exists at present. Only theoretical/hypothetic numbers can be used at present for this type of storage sites.

2) The best opportunities for saline aquifer storage are linked to hydrocarbon

prospects (e.g. aquifer below oil/gas field; aquifer within a petroleum basin that might contain undiscovered hydrocarbon reserves) and hence require collaboration with the petroleum industry. CO2 sequestration would be accepted only when potential interferences between both activities were minor (e.g. non-hydrocarbon-prone structures) or positive, i.e. revenue generating (e.g. EOR/EGR). Moreover, the latter sites are much better characterized (less exploration costs) and already have infrastructure installed. If individual structures are small-scale and infrastructure is not yet installed, CO2 storage becomes quite expensive. Also, off-shore development is much more expensive than on-shore. Practically, only commercial-scale (injection of at least 30-40 Mton CO2 over 20 years) storage projects in off-shore saline aquifers (without other benefits) would make economic sense if on-shore capacities are not sufficient.

3) Storage in mature or depleted oil and gas fields could be combined with the

economic benefit of EOR or EGR and with the presence of infrastructure and detailed exploration data to be less expensive than other storage options. However, (i) the capacity of individual fields is limited (on the order of a few Mton to a few tens of Mton CO2 for the largest known fields). Also (ii) timing is crucial; a “use or lose” rule here can be applied. Old abandoned fields require make-over of wells which is highly expensive and poses problems with well integrity. Ideally, the wells are used directly during or after oil recovery ceases (keeping maintenance costs minimal). The abandonment procedure of active wells can be prepared for cases of long-term CO2 storage. In the case of EOR (iii) the seal should be checked for potential gas leakages (different than for oil/water).


88

The cost of adding CO2 to the oil reservoir has to be compared with the revenues from enhanced oil recovery and can vary greatly according to the oil price and the cost of getting CO2 to the injection site. The CO2 utilization factor is approximately around 0.2 - 0.3 ton CO2 / barrel oil produced in cases where injected CO2 is recycled and again reinjected (Holtz et al., 2005; McCoy, 2008). When external CO2 is injected continuously (without recycling) the rates can be much higher (Evans, 2009). The extra oil recovery would typically amount to 10-20% of the original amount of oil present. After recovery, pure sequestration of CO2 can be carried out.

4) Although storage in coal answers only small demands because of the limited

injectivity in coal, the storage potential could be relevant when economic benefits can be obtained from CO2-enhanced coal bed methane recovery (ECBM). In that case, the coal strata could become an interesting opportunity for local small CO2-point sources. Some countries (like Botswana and Zimbabwe) show excellent CBM perspectives and attract industrial investors. The exceptional coal seams in the Kalahari Basin are compared with the world-class coal in the San Juan Basin in the USA64. If this industry would develop fast to a mature business and CO2 can efficiently contribute to gas recovery, then CO2 injection could even generate a net income (depending on the CH4 and CO2 price), as the main infrastructure is already developed for CBM recovery. Note also that ECBM is one of the safest sequestration methods thanks to the physical-chemical adsorption of CO2 onto the coal surface, provided that no future mining would take place in the same coal. As CBM requires deeper coal depositions than is used for conventional coal mining, which targets shallow coal, these are not competing activities. In the highest potential CBM areas, one could expect to store up to 25-30 Mton CO2 over 20 years at low cost or small profit (Gale, 2004).

3.1.3. STORAGE CAPACITY IN THE BALKAN REGION

Exploration opportunities

The geology of the selected Balkan region is dominated by the Carpathian and Alpine orogenies that result in a quasi circular mountain chain surrounding the Pannonian Basin (Figure 25). The Pannonian Basin groups several subbasins and hosts oil and gas fields. It could also contain various non-hydrocarbon prone storage structures. In general the structures in the Pannonian Basin are relatively small65 (on the order of one to a few Mton CO2-storage capacity; Fig. 27). The Albanian petroleum structures, which formed in a geologically different setting, are larger with several fields

showing storage capacities above 10Mton CO2.i

64

Reeves,S., Oudinot,A., The Allison Unit CO2 ECMB Pilot –a reservoir and economic analysis 65 (USGS, undiscovered field size distributions; Dolton, 2006).


89

Figure 25: Main tectonic units of Alpine fold-and-thrust belt and Alpine-Carpathian-Dinaric Mountains. The Pannonian Basin groups several subbasins.

Source: Dolton, 2006. USGS Bulletin 2204-B

Figure 26: (Left) Existing and undiscovered hydrocarbon fields in the Pannonian Basin (Right) Hydrocarbon fields in Albania with indication of some larger finds

Source: USGS.


90

The oil and gas fields in the Albanides are generally larger than the Pannonian field sizes (Figure 26). This makes the Albanian depleted fields more suitable for CO2 storage.

Country summaries: For full storage resevoir matrix see Table 124 in Annex A.

Albania:

Two viable storage options can be identified for Albania, one of which relates to drilling and leaching into a large salt dome. The salt structure is located at Dumre and covers a surface area of 12 by 18km. Several wells or caverns would be required for relevant storage capacities. 1 Mton CO2 per well could be stored with a total maximum capacity between 20 – 50Mton. However, the limited capacity per well makes this an expensive option. A second storage option is the use of depleted oil/gas fields. However, only fields that are being depleted or will deplete within the future timeframe considered in this analysis are qualified for the purposes of this study. Oil production in Albania has been declining since 1990 and since 1983 EOR has been used in mature fields (injection of between 820 – 10.076 tons CO2 per field) to recover extra amounts of petroleum. The potential for EOR should be evaluated and the abandonment history for the hydrocarbon fields should be researched in order to estimate the effective storage capacity. Moreover, there is still active exploration for hydrocarbons both on- and off-shore in Albania and in 2008 a large oil/gas field was reported close to Kosovo.66 Total oil reserves are estimated at ~198 MMBO and gas at ~0.03Tcf. The EU Geocapacity Report calculated a total of 111 Mton CO2 effective storage capacity in the currently known and active fields. This total amount however is distributed over various smaller fields. Nevertheless, compared to the reservoir sizes in the Pannonian Basin, the Albanian fields are relatively large (5 fields showing storage capacities of over 10Mton CO2, but less than 30Mton CO2). Data for estimating the storage capacity in saline aquifers are lacking and full exploration would be required in order to identify a potential storage site. Storage in coal is not an option for Albania due to the type of coal available and the future mining plans.

Croatia:

Storage capacity has been identified in Croatia in both (depleted) oil/gas fields and saline aquifers. Oil production has been on the decline since 1994 and EOR has already been applied in three fields. The additional potential for EOR/EGR should be evaluated and the abandonment history of producing fields should be known in order to estimate the effective storage capacity under economically beneficial conditions. Exploration is still ongoing and estimates of undiscovered reserves range between 41 and 145 MMBO and between 34 and 180 BCFG for oil and gas respectively. The storage capacities for individual oil fields are generally smaller than those in Albanian fields, with most fields representing a capacity below 2 Mton CO2. Gas field sizes are slightly larger with an estimated 15% representing storage capacity between 5 and 20 Mton CO2. Also for storage in saline aquifers several uncertainties need to be investigated in order to make reliable capacity estimates. Although some structures have been inferred, relatively large exploration efforts are required to confirm storage capacity.

Serbia:

The hydrocarbon reserves in Serbia amount to about 78 MMBO for oil and 1.7Tcf for gas. Oil production has always been minor and is slowly declining. Individual fields are small-sized with

66

Lendman, 2008; http://www.globalresearch.ca/index.php?context=va&aid=8129).


91

most representing storage capacities below 2 Mton CO2. Undiscovered reserves are estimated between 23 and 82 MMBO for oil and between 19 and 103 BCFG for gas. CO2 injection could be considered for EOR purposes. Apart from the hydrocarbon fields, potential storage capacity would be located in saline aquifers from the Vardar Basin, but the detailed data neceassary for accurate estimates are lacking.

Bosnia-Herzegovina:

There might be storage capacity in the order of 200Mton CO2 in saline aquifers from the Sarajevo-Zenica basin, but an extensive exploration survey would be required in order to prove sealing and effective storage capacity.

Macedonia:

An effective storage capacity estimation of approximately 400Mton CO2 has been made for the East Vardar Basin. Further exploration is needed for site characterization.

Kosovo, Montenegro:

Due to lack of data no storage potential could be identified and full exploration would be required. However, a large oil/gas field was found in Albania close to the border with Kosovo in 2008.

3.1.4. STORAGE CAPACITY IN THE SOUTHERN AFRICA REGION

Exploration opportunities

The main reservoir opportunities in Southern Africa relate to either the petroleum or coal basins. The oil and gas prospects are located on-shore close to the coast and off-shore. Rifted blocks from several ages contain reservoir, source and sealing rocks in geometrical trap situations providing hydrocarbon-bearing fields and storage opportunities. Although belonging to different basins, a semi-continuous rim of hydrocarbon fields surrounds the coasts of Namibia, South Africa and Mozambique. Depending on the size of the rifted blocks and substructures, small or larger oil/gas fields have been formed. The following figures show the distribution of petroleum basins in the studied region. Excellent quality coal deposits are found in the Southern Africa region (Figure 27). Due to its shallow depth, coal has been mined mainly in the South Africa Karoo Basin. Where the coal occurs at larger depths coalbed methane (CBM) extraction becomes an option. This is the case for instance in the Great Kalahari Basin, which spreads out largely over Botswana and minor parts of Zimbabwe, Namibia and South Africa.


92

Figure 27: Overview of hydrocarbon fields off-shore in South Africa with indication of seismic coverage and typical structure to be expected. The on-shore opportunities relate to coal

Source: Petroleum Agency SA


93

Figure 28: Location of off-shore petroleum basins (Zululand which continues to Mozambique basins; Durban, Outeniqua, Orange which continues in Namibia basins)

Source: Petroleum Agency SA (2008)


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Figure 29: Location of off-shore petroleum basins in Namibia (left) and Mozambique (right)

Source: NAMCOR 2003 (left) / GEO ExPro March 2006 (right)

Figure 30: The Karoo Supergroup in Southern Africa in the Main Karoo Basin of South Africa and the Great Kalahari Basin ( labelled in yellow) covering Namibia, Botswana, Zimbabwe and South Africa

Source: Masters thesis of Segwabe, 2008 (modified after Bordy, 2000 and based on Johnson et al., 1996)

Country summaries: For full storage resevoir matrix see Table 125 in Annex A.


95

South Africa:

A large effort in storage option identification has already been made in South Africa with the CCS Atlas and Technical Report as the result. New exploration would be required in order to answer remaining questions and uncertainties. The highest storage potential is situated in the off-shore Mesozoic Basins, which are currently explored also for hydrocarbons. Storage in these locations would require interaction and cooperation with the petroleum industry. The use of CO2 for enhanced oil or gas recovery (EOR/EGR) from the fields in production should be evaluated. Furthermore, the depletion history of the developing fields should be correlated with CO2 sources in order to assess the amount of CO2 that can be stored under economically beneficial conditions (EOR/EGR or depleted fields where infrastructure can be reused for the CO2 storage). Non-hydrocarbon-prone structures within the same basins require further exploration and communication with the petroleum industry before development. However, the off-shore location involves higher development costs. On-shore in South Africa, the Algoa and Gamtoos subbasins forming part of the Mesozoic Outeniqua Basin, might contain non-hydrocarbon prone structural closures. More exploration is required to assess the effective storage capacity of these basins. Further onshore, the very extensive Karoo Basin unfortunately is not suitable for CO2 storage due to low injectivity, shallow depth, lack of geometrical closures and unsure containment. Although South Africa has vast coal reserves, CBM exploitation is still in the exploration phase. Only the deeper parts of the coal basins (ideally 800-1000m) would be convenient for CO2-enhanced gas extraction (ECBM).

Botswana:

The storage capacity in Botswana is not well defined, mainly because of lacking exploration data. Nevertheless, coal deposits have been explored and there has recently been a significant interest for CBM extraction by mining companies (Rodgers, 2010). Preliminary exploration and appraisal surveys have proven world-class reserves. Although this industry is still in its infancy in Botswana, it might become a fast-growing industry with a potential for CO2-ECBM on the long-term. Since the coal deposits are compared with those from the USA San Juan Basin, numbers could be extrapolated from these and comparable (e.g. China, Australia) projects for the purposes of the generating storage capacity estimates.

Mozambique:

Mozambique’s onshore storage potential is largely unexplored. Geological exploration has concentrated on the offshore hydrocarbon basins, the Rovuma and Mozambique basins. The gas fields that are currently being mined today could be used for CO2 injection in the future (approximately within 20-25 years) with the storage capacity depending on the field size. In total, a maximum of about 100Mton CO2 could be expected to be stored in these fields. Non-hydrocarbon-prone reservoirs in the same basins could also be used for storage. However, these options require more exploration, involve higher development costs, (as no infrastructure can be reused and they are in an offshore location) and communication with the petroleum industry.

Namibia

The Namibian situation can be compared with Mozambique’s in that the exploration focus has been on off-shore hydrocarbon fields that are rather well-known at present. Operations have not yet begun on the large Kudu field, but production is expected to start in the coming years. The depth and off-shore location makes development relatively expensive. The onshore sedimentary basins are not sufficiently explored for capacity assessments and coal deposits are too shallow for CO2-ECBM purposes.

Zimbabwe


96

Promising CBM reserves have been inferred recently in the coal strata in Zimbabwe. If a CBM recovery business rapidly took off and ECBM showed to be an economically viable option there, then a capacity of about 5 Gton CO2 (Gale, 2004) can be put reasonable estimated.

Tanzania, Zambia:

These countries need greater exploration efforts to identify adequate storage options. Among the available geological data and current activities, no evident storage options can be identified.

CHAPTER 4 Identification of cost elements

97

CHAPTER 4 IDENTIFICATION OF COST ELEMENTS

4.1. ASSESSMENT OF CCS CAPTURING TECHNOLOGIES AND COSTS

4.1.1. COMPILATION OF LITERATURE FINDINGS FOR DIFFERENT CAPTURING TECHNOLOGIES

The data in Table 45 provide estimates of the costs of the fossil fuel plants with and without CCS, developed through an extensive literature review67. CO2 capturing technologies are only operational at a number of demonstration plants and a lot of research is devoted to improving these capturing technologies and reducing the penalty in net power output to the grid and overall resulting efficiency. The figures include assumptions on the improvement of the technologies but do not assume any revolutionary breakthroughs. As for all emerging technologies, uncertainty on performance evolution is significant. For the CCS integrated plants, the cost and capacity figures here include CO2 capture, but not transportation and storage. These elements are accounted for in each plant represented in the model individually, and the method for how this is carried out is explained in detail in later sections of this report. For post combustion capturing and IGCC, it is assumed that the CCS integrated plants are identical to the respective reference plant with out CCS, interms of the amount of electricity they produce. There is a loss of capacity and efficiency due to the parasitic load, which is the energy required to run the capture unit. The figures from the literature are assumed to be relevant for the European Area and have been adapted for other regions so as to be used as inputs in the model (see 4.1.2.)

67 IEA (2008a) Energy Technology Analysis, CO2 capture and storage, a key carbon abatement option, International Energy Agency, Paris (France) -IEA (2008b) Energy Technology Perspectives 2008, Scenarios and strategies to 2050, International Energy Agency, Paris (France) -IEA GHG (2007) CO2 capture from medium scale combustion installations, International Energy Agency, Greenhouse Gas R&D Programme, Report Number 2007/7 -Davison J. (2007), Performance and costs of power plants with capture and storage of CO2, Energy 32,p1163-1176 -“Policy Support System for Carbon Capture and Storage”, Kris Piessens, Veerle Vandeginste, Kris Welkenhuysen (RBINS), Ben Laenen, Roland Dreesen, Johan Bierkens, Matsen Broothaers, Sandra Hildenbrand, David Lagrou, Wouter Nijs (VITO), Philippe Mathieu, Emmanuelle Bertrand (ULg), Jean-Marc Baele (FPM), Chris Hendriks, Erika de Visser, Ruut Brandsma (ECOFYS), September 2008, http://www.belspo.be/belspo/ssd/science/Reports/PSS-CCS_FinRep_2008.DEF.pdf

http://www.belspo.be/belspo/ssd/science/Reports/PSS-CCS_FinRep_2008.DEF.pdf


99

Table 45: Technical and economical characteristics of reference power plants and CCS integrated power plants (see footnote 68) Parameter

Reference coal plant

(supercritical)

Reference gas

plant (NGCC

)

PC plant with post-combustion capture

NGCC plant with post-combustion capture

Reference IGCC

IGCC with capture

Reference oxy-coal plant with capture

Oxy-gas plant with

capture

PC NGCC

PC-CA capture

NGCC-CA capture IGCC

IGCC capture

Oxy-coal capture

Oxy-gas capture

Production Capacity

510 480 427 412 488 436

Availability

85.5 89.5 85.5 89.5 85 85 85.5 89.5

Net efficiency

47 57 38 49 44 35 37 48

Capture efficiency

--- --- 85 85 --- 85 90 95

CO2 pressure

--- --- 137 137 --- 137 137 137

Investment $/KW

2072 789 3052 1232 2184 2856 3136 1483

VOM $ /GJ electricity

3.34 0.78 3.67 0.95 1.67 1.83 1.59 0.99

FOM $ /kw yearly

39.10 14.78 45.68 18.81 48.87 57.10 58.78 19.75

Life Time

40 30 40 30 30 30 30 30

Year of investment

2010 2010 2010 2010 2010 2010 2020 2020

Year of efficiency

2010 2010 2010 2010 2010 2010 2020 2020


100

4.1.2. ADAPTATION OF THE COST ELEMENTS TO THE LOCAL CIRCUMSTANCES

Since these cost estimates are for the European area, it is necessary to adapt them to reflect local costs in the case study regions of the Balkans and Southern Africa. Different methodologies can be used to adapt the costs to local circumstances: Deriving a correction factor from existing, similar technologies: This can be carried out, for instance, by comparing the investment cost for an existing PC or CGGT plant in Europe, in the Balkan region, and in the Southern African region, and scaling appropriately. Without access to local information this involves the risk of a circular reasoning, i.e. that we will compare prices originating from the same source. Decomposing in labor and materials costs. International sources like the International Labor Organisation and the World Bank publish figures on labor costs and material costs in different countries worldwide. By decomposing the cost of an electricity production plant into labor and materials costs these figures can be used to calculate country correction factors. This method involves two problems. First, this requires detailed knowledge about the different weights of the different labor and material components considered. Second, the production methodologies might be different (for instance in the construction sector) due to relative differences in labor and capital cost. Scale based on purchasing power parities Purchasing power parity (PPP) is the ratio of the cost of a basket of goods in one country to a reference country. In poor countries the PPP of non-traded goods is almost always lower than the exchange rate. The difference between the exchange rate and the PPP rate is an indication for the difference of the cost of living. The World Bank compiles GDP PPP rates on a regular basis, and in the World Bank 2005 ICP project the Purchasing Power Parities for different types of products have been compiled for all the countries considered in this study (except Zimbabwe). We observe that the GDP-PPP is much lower than the exchange rate. This indicates that in general the cost of living is much cheaper compared to in the US. However, for machinery and equipment the difference between the exchange rate and PPP is much smaller and often exceeds the exchange rate. The logical explanation for this observation is that machinery is not locally produced but imported at world prices. We therefore propose to use WB 2005 machinery and equipment PPP figures to convert investment costs. These figures are given in Table 46. Depending on the currency used in the model, one of the following formulas should be used. Model expressed in local currency:

Investment cost = Investment cost in Table 45 * PPP Machinery and investment Model expressed in US dollar:

Investment cost = Investment cost Table 45 * PPP Machinery and investment /Exchange rate


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Table 46: Exchange rates (2005 LCU/$) and Purchasing Power Parities for GDP, Machinery and Equipment and construction costs in South African and Balkan region

PPP

Exchange rate GDP Machinery and

equipment Construction

Botswana 5.11 2.42 3.65 1.99

Mozambique 23323 10909.45 25985.66 14746.5

Namibia 6.36 4.26 … …

South Africa 6.6 3.87 6.09 4.08

Zimbabwe 33068 … …

Albania 100.78 48.56 108.46 56.86

Bosnia and Herzegovina 1.57 0.73 1.76 0.72

Croatia 5.95 3.94 6.46 3.76

Macedonia 49.3 19.06 50.81 16.14

Montenegro 0.8 0.37 0.91 0.37

Serbia 65.72 27.21 57.28 23.08

4.2. ASSESSMENT OF TRANSPORT COSTS

Pipeline transport of CO2 is more cost-effective than trucking or sea shipping for distances below 1,000 km (IPCC 2005). The IPCC estimates the cost of a 250 km onshore pipeline transport at a mass flow rate of 10 Mton/year at between 1.5-2.5 USD/tCO2 depending on the terrain conditions. For a mass flow rate of 20 Mton/year, unit costs are estimated in the range 0.8-1.2 USD/tCO2. For a mass flow of 5 Mton/year the costs are estimated in the range 2.2-3.8 USD/tCO2. Increasing returns to scale are explained by the required diameter and the specific structure of the investment cost.

Figure 31: CO2 pipeline diameter in function of the mass flow

Source: Based on Hendriks et al. 2003 for a length of 100 km

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Investments are higher when compressor stations are required to compensate for pressure losses. Distances up to 250 km can be realized without compression station. Longer distances are feasible without compression station by increasing the diameter. In the models, transport costs are a function of location of suitable storage places and localization of electricity plants. The assumptions are given in chapter 5.

4.3. ASSESSMENT OF STORAGE COSTS

4.3.1. METHODOLOGY

A wide variety of cost parameters and factors are involved in cost calculation for CO2 storage projects. The life-cycle of a storage project, shown in Figure 32, encompasses (i) the pre-injection phase where further exploration and/or site characterization needs to be performed, (ii) the development phase with drilling, completion and testing, (iii) the injection phase with operational costs and regular/continuous monitoring, (iv) the post-closure period where monitoring continues until permanent containment is proven and transfer can be considered, and finally (v) the post-transfer or abandonment stage, where responsibility is passed over to the competent authorities.

Figure 32: Summary of CO2-storage life-cycle phases and milestones

Source: EU CCS-Directive 2009/31/EC

The main cost drivers in several of these phases are drilling and seismic surveys. These costs were requested from companies in both regions to use as inputs in the model. The results from these inquiries, however, revealed to be highly uncertain and variable, mainly due to lack of commercial activity in some regions, the remoteness of some areas, or just lack of expertise in deep drilling. It is highly likely that CCS would develop with a close relationship to ongoing commercial activities such as hydrocarbon extraction, EOR or ECBM, rather than in remote places where this does not take place. It can therefore be assumed that competitive prices for drilling and seismic acquisition would apply. Instead of using the prices obtained from the countries directly, which were wide ranging and from a number of different sources, estimates from RISC (CO2 Injection Well Cost Estimation, Carbon Storage Taskforce, 2009) have been used as a standard costs for wells on- and off-shore, and costs for seismic surveys have been used from the African estimates. The same numbers for Southern Africa and the Balkan region have been used, allowing for consistency across the region and transparency of approach. This is reasonable considering the significant uncertainties associated with storage capacity estimates, and so using the same cost estimates likely falls within the error bounds of the study. Since the injectivity is a parameter that is lacking in most of the identified storage options and this parameter determines the amount of wells needed for a storage project of

Phase 1

Assessment

•Assess storage

potential

•Define storage

sites and

exploration

requirements

•Review

exploration permit

applications

Phase 2Characterisation

Review of storage

permit applications

(Compliance with

all requirements of

Directive,

considering

opinions of

Commission)

Phase 3

Development

Phase 4Operation

Phase 5

Post-Closure/ Pre-Transfer

Phase 6

Post Transfer

•Oversight of any

baseline monitoring

& reporting

•Approval of any

updates to

monitoring &

corrective

measures plans

•Inspections

•Review of storage permit

•Oversee monitoring

& reporting•Approve

monitoring/CM plan updates

•Ensure corrective

measures •Periodic adjustment

of financial security

M2Award of

Storage Permit

M1 Award of

Exploration Permit

M3Start Injection

M4 Cease Injection/

Closure

M1

Award Exploration

Permit

M2Approval/Award

Storage

Permit

M4

Circumstance 1

Authorise Closure

Approve Definitive

Post Closure Plan

M5

Approve transfer to

MS

Release financial

security

MS takes

responsibility for

site

Circumstance 1•Continue inspections,

•Oversee

monitoring/reporting

•Approve of

monitoring/CM plan updates

Circumstance 2

•Take on operator

responsibilities for

monitoring, reporting,CM, updates to site

char, risk assessment,

and modelling

•Long term

stewardship by

Member States

•Monitoring to

detect leakages

•Conduct

corrective

measures, as

needed

•Surrender

allowances, as

needed

Phases

Major Project

Milestones

CA

Regulatory

Activities

CA

Permits and

Approvals

Circumstance 2

Decide to close

site after permit

withdrawal

M5 TransferResponsibility to

Member State


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a certain size, the total drilling cost is calculated as an order of cost, whereby the number of wells is defined based on an assumed injectivity. The relative storage cost expressed as USD/ton CO2 is influenced mainly by the size of the storage project, that is, the total volume stored. Since the size of individual structures is also an unknown in most defined storage options, a strategy was developed to estimate the expected size of individual projects. Subsequently, generic cost curves for each of the four CO2 resevoir types were obtained, with the price per ton as a function of the volume that can be stored. By combining these cost curves with the (expected) size of a project (i.e. looking up the position on the cost curve) a reasonable cost per ton can be deduced for each of the storage options.

4.3.2. SIZE OF STORAGE PROJECTS

The data used to determine the cost curves are based on the size distribution of known hydrocarbon fields and on datasets from USGS on undiscovered hydrocarbon reserves. These data were selected as a base because the oil and gas fields are hosted in a region-specific geology that is typically associated with structures of a certain size. Instead of trying to use the details per country and sub-region where they are available, a realistic size distribution based on a statistical analysis has been adopted. This allows for estimates to made of storage sites in the regions that have not been explored to a great extent. The graphs in figures 33 and 34 show the probability of a field of that size being found, as a function of the expected field size. In these graphs, the existing fields (i.e. all fields where data on size of individual reservoirs is available) have been represented with 100% probability of occurrence to indicate that these are real opportunities. The size distribution plot is based on the USGS datasets. They have size distribution curves for undiscovered oil and gas fields from the following countries of the case study regions: Croatia, Serbia and part of Bosnia-Herzegovina (grouped within “the Pannonian Basin”) and Namibia. The local geology and known fields are taken into consideration for their predictive models of undiscovered fields. The distributions should not be read as certainty that reservoirs of a named size are present, neither as though an infinite amount of very small reservoirs exist. They rather indicate the chance that when exploration was successful a field of a certain size would be found. Or in other words, in a certain geological setting more reservoirs of a certain size will typically be found. Where available, the existing field size distribution has also been plotted on the same graph to show the similar log normal distribution as the USGS reserve predictions. Size distributions of existing fields are provided in the FP6-Geocapacity report for Albania and Croatia.


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Balkan region

Figure 33: Size distribution of existing hydrocarbon fields and predicted undiscovered reserves for the Balkan region

Southern African region

Figure 34: Size distribution of existing hydrocarbon fields and predicted undiscovered reserves for the Southern African region

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undiscovered oil fields Pannonian Basin (USGS) undiscovered gas fields Pannonian Basin (USGS)

oil and gas fields Albania (GeoCapacity) oil and gas fields Croatia (GeoCapacity)

known fields Croatia (Geocapacity) known fields Albania (Geocapacity)

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undiscovered oil fields Namibia (USGS) undiscovered gas fields Namibia (USGS) known gas field Namibia (Kudu)

known gas fields Mozambique known gas fields Tanzania known gas fields South Africa


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4.3.3. COST CURVES

The following cost curves shown in Figure 35 to Figure 38 are based on specific assumptions taking into account the type of storage resevoir and its average characteristics (e.g. an average storage depth of 2,000m for off-shore hydrocarbon fields) within the studied regions. Instead of developing separate curves for each individual option storage option, the cost is estimated for several sizes of storage reservoirs for each storage type that reflect the several options identified and given in the reservoir matrices in Annex A. The assumptions made and the approach followed to calculate the cost curves for each resevoir type are summarized in Table 47.

Saline aquifer

Because most of the aquifer options show significant uncertainties, a pre-injection exploration phase has been taken into account in these cost curves. The level of exploration considered is dependent on the project surface area (mainly the length of the seismic surveys). The number of wells is based on the total volume to be injected and on an average injectivity of sandstone. Engineering, operation and management costs are considered as well as monitoring costs. For monitoring, a repeated seismic survey is foreseen as standard at the start of injection, after injection of 1 Mton, 5 Mton, 10 Mton, 20 Mton and at the end of injection. The rest of the monitoring costs are calculated as a fraction of the seismic cost. For post-closure, a fixed fraction is applied on the total project cost. The cost estimation exercise indicates that a 5-10 USD/ton storage cost would apply for larger on-shore projects (>20Mton). Smaller projects, especially those off-shore, have a higher cost per ton.

Figure 35: Cost curve for storage in on-shore saline aquifers with price as a function of the size of a project. Two different injection schemes are represented considering a CO2 injection flux of 2000 ton/day and 5000 ton/day respectively.

EOR / depleted field

For EOR and depleted oil/gas fields the costs have been calculated for different project sizes (<1 Mton, 1-5 Mton, 5-10 Mton, 10-20 Mton and >20 Mton CO2 stored). Based on these set volumes, the number of newly drilled injection wells and recompleted wells is assumed, together with eventual extra oil recovery. Make-over of existing wells has been calculated as 15% of the


106

investment cost for new wells. Monitoring and post-closure costs have been calculated in the same way as for saline aquifer monitoring.

Figure 36: Cost curve for storage in depleted hydrocarbon fields, with/without EOR/EGR. Note that no revenues from enhanced oil recovery are accounted for in the calculated cost. A conservative estimate of such revenues based on 8% recovery win and an oil price of 70 USD/bbl is indicated in green.

The cost estimation exercise shows that storage costs are between 5 and 10 USD/ton for larger projects (>10 Mton). Smaller projects involve higher costs per ton CO2 injected. The price offset that can be realized by EOR, on the contrary, is significant. In the shown exercise, a conservative price of 70 USD per barrel of oil has been considered and a conservative extra recovery of original oil in place (OOIP) of 8%. With these rather low numbers, a profit of about 40 USD per ton CO2 injected can be obtained. The potential for EOR thus largely influences the economic feasibility of a storage project.

ECBM

For the ECBM recovery case, the project is dimensioned on the CBM recovery set up. This means that a high density of wells is already present, which can be reused for injection of CO2. In some cases new wells would be required or adaptations to existing wells would be needed. Therefore, the cost estimate has been based on a standard project with 40 wells on a surface area of 60km2 with a life-time of 20 years and a total project investment cost of 60 million USD. These investments costs comprise 1.5 million USD per well for (drilling,) recompletion and operation. A crucial parameter for ECBM recovery CO2 storage projects is the injectivity of the coal, since this determines the total volume of CO2 that can be stored within the seams. Coal injectivities have been estimated to vary between 3,000 ton/well/year to 40,000 ton/well/year. Accordingly, a total amount of 2.4 Mton to 32 Mton of CO2 can be stored within the coal. The cost curve thus reflects the price variation as a function of the coal injectivity. For Botswana and Zimbabawe, where excellent coal properties have been reported for CBM recovery, a good injectivity (probably > 15,000 ton/well/y) may be assumed. This corresponds with a storage cost of 5-6 USD/ton CO2 or lower. No revenues from increased CBM gas production have been accounted for in this exercise. Such revenues could potentially off-set the storage cost. The


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Geological Survey of Botswana expects that 15-20% of the gas-in-place would be recoverable at a wellhead price of 2 USD/Mcf based on reservoir modeling.68 For the quantification of the benefits, a different approach has been used. Whereas the estimate for EOR was based on the amount for oil recovery and an assumption of the oil price, for ECBM it has been considered that N2 as an alternative to CO2 could also be used, and is therefore in direct competition. Consequently, a private company would always consider the cheapest solution. So although the value of the recoverd gas is much higher, (last years US gas prices averaged between 4 and 8.5 USD/Mcf) the potential benefits for ECBM have been quantified at 4.8 USD per ton CO2 injected.69

Figure 37: Cost curve for storage in an ECBM project as a function of total volume stored (i.e. according to the injectivity of the coal). Note: no revenues from enhanced CBM recovery are taken into account in this figure.

Salt cavern

Salt caverns have been used for more than a quarter of a century to seasonally store gases such as natural gas and hydrogen gas. After drilling, sweet water is circulated through the well in order to leach out the salt. The dried out cavern performs like an underground container with engineered geometry. Although this is a technically feasible technique, the long-term integrity has not yet been proven and its high investment costs make the use of salt caverns for non-commercial purposes rather unlikely (Bachu and Rothenburg, 2003; Gatzen, 2009).

68

http://www.gov.bw/Global/MMWER/dgscbmstudy.pdf 69

The CH4:CO2 ratio is between ½ and 1/3. Reeves and Oudinot estimate the cost for purification as 0.25 €/GJ.

Taking the lower ratio, a gas price of US$4/GJ CH4 and appropriate unit converting and accounting for purification costs, a maximum CO2 credit of US$62/ton CO2 can be estimated. This figure leaves zero profit for a private company and should be considered as an upper limit unless a higher gas price is considered. However, a private investor will also consider the alternatives for ECBM, such as N2. Reeves and Oudinot (2005) estimate the price of N2 at US$11/ton. Given the recovery ratio of N2/CH4 is estimated at 1.3/1, then the alternative “feedstock” cost is only US$14.3/ton CH4. Therefore a private company will be prepared to pay US$14.3 for 3 tons CO2 (CH4:CO2 ratio) or US$4.8/ton CO2, which is the value assumed in this study. This figure can be considered as a conservative estimate.

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A total cost of 30 million USD has been estimated for a cavern with a storage volume of 1Mm3, which can be considered as a maximum size per cavern. An additional 18% on top of this investment cost has been estimated for monitoring and post-closure expenses. For larger storage projects, several caverns should be created. Lower investment costs have been assumed in these cases for the share of infrastructure. Nevertheless, the storage cost in any case would amount to over 30 USD/ton CO2.

Figure 38: Cost curve for storage in leached out salt caverns.


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Table 47: Assumptions made and approach followed to calculate cost curves per type of storage. *The Geological Survey of Botswana expects that 15-20% of the gas-in-place would be recoverable at a wellhead price of 2$/Mcf based on reservoir modeling.

COST ESTIMATION PER TYPE OF STORAGE

Approach Investments operation monitoring Post-closure

revenues

Saline aquifer exploration based on the volume to be stored length of 2D seismic survey and number of exploration wells

number of injection/control wells estimated in function of volume stored

project lifetime in function of total volume stored and injectivity

site development cost: drilling, engineering and plant installation in function of the number of wells to be drilled + pumps

O & M cost based on 8000h/y and project duration in function of the total volume and injectivity per well

Based on repeated 2D seismic survey at start, after 1, 5, 10, 20 Mton and at end

other monitoring cost as 15% of seismic cost

Estimated as 3% of total project cost

Not applicable

EOR/depleted field Average depth of wells 2000m

calculated for 5 size categories of projects: (E) capacity < 1Mton CO2 – production < 500 BOPD;

(i) 1-5Mton - < 500-BOPD;

(ii) 5-10Mton – 500-1000 BOPD; (iii) 10-20Mton – 500-1000 BOPD; (iv) > 20Mton - > 1000 BOPD

Cost of new injection well onshore 6M$, offshore 15M$;

number of new wells dependent on volume stored: 1 well for <5Mton CO2; 2 wells for 5-10Mton; 3 wells for 15-20Mton; 4 wells for > 20Mton CO2 project

recompletion of existing wells + operation costs estimated as 15% of new wells cost with number of recompleted wells dependent on oil production rates at onset of EOR: (E) 10 wells, (i) 10 wells, (ii) 20 wells, (iii) 30 wells, (iv) 40 wells

Based on repeated 2D (for onshore) / 3D (for offshore) seismic survey at start, after 1, 5, 10, 20 Mton and at end

other monitoring cost as 15% of seismic

Estimated as 5% of total project cost

Conservative assumptions: EOR 8% extra recovery and average oil price of 70$/bbl

produced oil volume equivalent to the set storage reservoir size as follows: mCO2 (Mton) = recoverable oil (Mm3) x CO2 density (0.7ton/m3 CO2) x oil formation volume factor (1.2)

the 8% win of recoverable oil x fixed oil price of 70$/bbl gives a fixed revenue per ton CO2 injected

In reality the oil price varies largely and the geologic characteristics of the reservoir determine the production win

ECBM CBM field lay-out with 40 wells over 60km2

project duration: 20 years

Volume stored depends on injectivity (= practical barrier); CO2 injection rates between 3,000 and 40,000 ton/well/year

1.5M$ / well (x40) for recompletion or new drilling and operation over project lifetime

repeated 2D seismic survey at start, after 1, 5, 10, 20 Mton and at end

other monitoring cost as 15% of seismic cost

3% of total project cost

Revenues are estimated at 4,8 $/ton CO2 injected

Salt cavern Maximum cavern size 1Mm3;

multiple caverns can be created in a single salt structure

Estimated actual cost per cavern of 1Mm3 is 30M$

larger projects: discount of 30% on investments costs

15% on total project cost

No seismics

Long monitoring !

3% on total project cost

Stored CO2 could be reproduced in the future when CO2 would be needed, but strong competition with H2 and CH4 that have much higher economic value

CHAPTER 5 Techno-economic model and simulations results

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CHAPTER 5 TECHNO-ECONOMIC MODEL AND SIMULATIONS RESULTS

5.1. GENERAL MODEL DESCRIPTION

For techno-economic modeling and optimization of the development of power systems, the MESSAGE model with built-in features for multi-regional development and scenario analysis was used. Each country was modeled as a separate system and connection between regions were set at multi-region level. MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impact) was developed by IIASA and IAEA. In first approximation a model built using MESSAGE could be labelled a physical flow model. Given a vector of demands for specified energy goods or services, it assures sufficient supply utilizing the technologies and resources considered. MESSAGE is a systems engineering optimization model used for medium-to-long-term energy system planning, energy policy analysis, and scenario development. The model provides a framework for representing an energy system with all its interdependencies from resource extraction, imports and exports, conversion, transport, and distribution, to the provision of energy end-use services such as light, space conditioning, industrial production processes, and transportation. Scenarios are developed by MESSAGE through minimizing the total systems costs under the constraints imposed on the energy system. Given this information and other scenario features such as the demand for energy services, the model configures the evolution of the energy system from the base year to the end of the time horizon (year by year or in longer time steps, as defined by the model user). It provides the installed capacities of technologies, energy outputs and inputs, energy requirements at various stages of the energy systems, costs, and emissions, among other parameters. The degree of technological detail in the representation of an energy system is flexible and depends on the geographical and temporal scope of the problem being analyzed. A typical model application is constructed by specifying performance characteristics of a set of technologies and defining a Reference Energy System (RES) to be included in a given study/analysis that includes all the possible energy chains that the model can make use of. In the course of a model run, MESSAGE then determines how much of the available technologies and resources are actually used to satisfy a particular end-use demand, subject to various constraints, while minimizing total discounted energy system costs. The time horizon of the study is 2015 to 2030, and annual resolution in simulation/optimization has been used. By default, minimization of the total system costs is the criterion used for optimisation of the model developed using the MESSAGE. The total system cost includes investment costs, operation cost and any additional penalty costs defined for the limits, bounds and constraints on variables. For all costs occurring at later points in time, the present value is calculated by discounting them to the base year of the case study. The sum of the discounted costs is used to find the optimal solution.


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5.2. OPTIONS FOR MODELING CCS IN TECHNO-ECONOMIC OPTIMIZATION MODELS

In this section a description of general options for the modeling of CCS in techno-economic optimization models is provided. In the first sub-section, the representation of technologies in the model is briefly described. In the next sub-sections, a basic modeling approach is first described and then modeling more detailed approach, with a more refined way of representing of capturing, transport and storage of CO2. Some additional potential add-ons to that basic approach are also described. For this study, the latter, more detailed representation for CCS has been used for the modeling exercise, together with some of the add-ons discussed (Stepwise transport and storage cost).

5.2.1. TECHNOLOGY DATA

CO2 Capturing technologies

For new build plants with CCS, one can consider post combustion capturing, pre-combustion capturing and oxy-fuel technology options explicitly. For retrofitting existing plants, post combustion capturing and oxy-fuel technologies only can be considered. The best choice depends on the original design of the plant. Post combustion capturing technology requires a huge amount of heat for the regeneration of the solvents. Estimates are in the range 2.7 and 3.3 GJ/ton. For a SCPC plant this means that approximately 25 % of the heat produced in the boiler is required in the capturing process. This heat can be delivered at economic conditions if the plant can be designed as a CHP plant, requiring specific dimensioning of the boiler and turbines. Another consideration relates to flue gas impurities. SO2 and NO2 degenerate the solvent and very low concentrations are desirable to avoid excessive losses of solvent. If the existing purification device is not sufficient, the additional cost of a replacement purification device might be prohibitive. Oxy-fuel combustion capturing could be an alternative option for retrofit. Considerations should be made about the boiler geometry and the recycling of CO2. Flame temperatures and heat capacity of gases to match fuel burning in air occurs when the feed gas used has a composition of approximately 35% by volume of O2 and 65% (as compared to 21% in air) by volume of dry recycled CO2. These characteristics have an impact on the optimal boiler geometry. For the representation of the CO2 transport network in the model, different options for trunk pipelines, satellite pipelines, and direct connections can be considered. An alternative, simpler approach is to consider a standard transport cost per ton CO2. These options are further developed in section 5.2.2 for the “basic approach”, and in section 5.2.4 on an “extended approach”.

Storage

Individual storage sites, with given characteristics (total capacity, injection rate, specific monitoring requirements, expressed as monitoring costs) are considered (see Tables 124 and 125 in Annex A). Storage capacity limitations set an upper limit to the cumulative CO2 emissions that can be stored and thus to the activities of the corresponding power plants over the years. Storage costs have been adapted to local circumstances, as per the explaination in section 4.1.2.


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5.2.2. BASIC APPROACH: DEDICATED CONNECTIONS

Characteristics

In the “dedicated connections” approach, one source (a power plant for example) is coupled only to one sink. For new plants one can consider the three capturing technologies explicitly and leave it to the model to make the best choice. Alternatively, as a first approximation, one can consider one generic capturing technology using average performance figures. Individual power plants are represented in the model by a number of characteristics, such as their capacity. This basic modelling approach should take into account the following aspects:

Individual plants (new plants and a selection of existing plants, based on ex-ante study of logical sites);

Excess sink capacity (preferred sites have sufficient sink capacity, preferably more than the plant will emit during its lifetime);

Generic capturing technology;

Transport via dedicated pipes (1 source- 1 sink).

General approach

Promising sink locations were identified from the reservoir matrix that was developed through extensive research on potential storage sites (Tables 124 and 125 in Annex A). Practically, these are marked in green and yellow in the Tables. For each of these sink locations, a suitable location for a new electricity plant can be determined. This location might be based on other considerations (availability of water, connectivity to the grid, availaibity of coal transport infrastructure, presence of existing electricity production, legal constraints) and determine the distance to the sink for quantifying transport costs. The maximum plant capacity for the particular nearby sink, taking into account its estimated storage capacity, must also be determined. This is based on the principle that the storage capacity should be sufficient for the whole lifetime of the new installation. The maximum plant capacity is given by formula (1). This maximum capacity should be introduced into the model as a limit on investement for this new electricity plant. The model will determine the installed capacity, which will be less than the maximum plant capacity calculated by the formula.

Max plant cap (MWel) = RF * total storage capacity (Mton)* Eff /( Life * Fef *AF *Capf) (1)

RF : Reserve factor to take care of uncertainty in storage capacity estimation (value 0.1- 0.8) Eff: Conversation efficiency of plant, net or gross depending on modeling approach (see next section) Fef: Fuel emission factor expressed in Mton CO2 / PJ fuel Life: Lifetime of new plant, expressed in years AF: Plant availability factor (= 0.85) Capf: Capacity conversion factor (PJ/MW = 0.031536)

Integrated CCS –electricity plant

A simple but methodologically correct way to model CCS is to consider integrated plants with CCS. An integrated plant treats electricity production, CO2 capturing, CO2 transport and storage as one electricity producing technology. An integrated CCS – electricity plant is characterised by a plant


113

specific CO2 emission parameter, and an appropriate efficiency parameter taking into account the electricity consumption of the capturing, transport and storage of the CO2. Values for Eff, the efficiency of the plant as used in forumla (1), are proposed in Table 45. All investment and variable costs related to the capturing, transport and storage are included in the operational values of the plant. This approach is a simplification and therefore assumes that:

The transport and storage costs are proportional to the tons of CO2 and remain constant over time;

The storage facility is sufficient for the whole lifetime of the plant and the storage capacity determines the maximum capacity (MW) of the new plant;

The transport uses a dedicated pipeline, not a CO2 network with different connection points;

Optimisation of the transport is not included;

Lifetime of all different components are the same. A practical consideration for reporting is that avoided CO2 emissions and stored CO2 emissions cannot be calculated directly by the MESSAGE model. Besides its simplicity, this approach has also the advantage that no additional considerations regarding the capacities of the different subsections (power plant, transport and storage) are required. This model structure can also be adapted for modelling CCS retrofitting on existing plants. In this case the reference Supercritical Power Coal installation represents the existing installation and should be characterised with the residual life time and the current characteristics (efficiency, availability, variable and fixed operationg costs). The SCPC plant with CO2 Capture represents the same plant equipped with CCS. The lifetime of the SCPC plant with capture should be limited to the residual lifetime of the existing plant. In the MESSAGE model, investment costs are only accounted for in new plants, and so for existing plants they can be omitted. However, the cost of retrofitting with CCS should be accounted for in the plants with CO2 capture. One additional constraint (not visible on the figure) is that it is necessary to limit the global capacity of the SCPC reference plant and the SCPC plant with capture. This way of representing CCS in the MESSAGE model is shown in Figure 39.

5.2.3. EXTENDED APPROACH: SEPARATION OF CAPTURE, TRANSPORT AND STORAGE

A more detailed way of representing CCS would be to break out the capture, transport and storage individually. This is the approach taken in this study, and ot is shown schematically in Figure 40. When modelling CCS retrofit for existing plants, the model must have the option of selecting whether to invest in the retrofit capturing option or not. The so called CCS-Ready plants are the most suitable for retrofitting. Some minor modifications in the original design of the plant might have a significant impact on the cost and performance of the retrofit. Additional costs for making a new plant CCS-Ready are estimated between 0.5 % and 28 % of the original plant costs 70. Dimensioning of the capturing facility is crucial and care should be taken to model this correctly. One particular problem stems from the fact that the capacity of the plant is given, but the utilization is determined by the model itself. The dimensioning of the capturing, transport and storage facilities should be based on the existing capacity (or maximum utilization) and not on the current utilization. For base load capacities this does not pose any problems as the current

70

ICF International, Defining CCS ready : An approach to an international definition (2010)


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utilization equals the maximum utilization. In most cases it is sufficient to perform a consistanty test on the model results. There can be a dimensioning problem, however, if the power plant is operating below its full capacity. For simplicity, in Figure 39 and Figure 40 only the physical energy flows have been represented. The MESSAGE model also represents various other characteristics, such as existing capacities, liftime, investment cost, variable and fixed operational costs. In the figures, a coal plant without and a coal plant with capturing technology are shown. Besides these coal plants there are also alternative options for producing electricity in the model. In the diagrams, wind and NGCC are shown as examples of alternative technologies. Lines with two arrows represent equality conditions. The first process is a dummy process, representing the existing chimney, allowing for the alternative of not installing CCS. This structure can also be used for new plants.


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Figure 39: Representation of an integrated CCS-electricity plant in the model

Purchasing coal

(€ /GJ)

Reference SCPC plant

without capturing(GJ electricity)

Electricity demand

Industry

Electricity demand

Residential

Electricity demand

Other sectors

SCPC plant with capturing

(GJ electricity)

CO2 emitted

(ton CO2)

wind

2.22 GJ coal 1.00 GJ electricity

0.215 ton CO2

NGCC plant(GJ electricity)

Purchasing gas

(€/GJ)

2.70 GJ coal

1.00 GJ electricity

0.039 ton

CO2

Reference SCPC plant:

efficiency 45 %

Investment cost 14 €/kw

Fixed opertaional costs

Variable costs

Mac capacity: no constraint

SCPC plant capturing:

Efficiency 37 %

Investment cost: Reference plant

+ capturing technology

+ transport

+ storage

Max capacity : see(1)

1.90 GJ coal 1.00 GJ electricity

0.109 ton CO2


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Figure 40: Representation of an integrated CCS-electricity plant in the model - a more Detailed approach

Purchasing coal

(€ /GJ)

SCPC plant (existing)(GJ electricity)

Electricity demand

Industry

Electricity demand

Residential

Electricity demand

Other sectorsCO2 emitted

(ton CO2)

wind

2.22 (GJ coal) 1 GJ electricity

0.215

(ton CO2)

NGCC plant (GJ electricity)

Purchasing gas

(€/GJ)

SCPC plant existing:

Figures derived for following assumptions

Efficiency SCPC plant 45 %

Carbon content of coal : 0.0927 ton CO2/GJ

NGCC plant:

Efficiency NGCC plant 57 %

Carbon content gas 0.0558 ton CO2/GJ

Capturing

(ton CO2)

CO2 storage

(ton CO2)

Chimney(ton CO2)

CO2 transport

(ton CO2)

1 1

0.85

0.15

1.00

1.2 GJ el

1.75 GJ gas 1.00

0.0979 ton CO2

Equal row

1 1


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5.2.4. POTENTIAL EXTENSIONS TO THE MODELING APPROACHES

Detail on the capturing technologies

For new plants, the generic capturing technology could be replaced by the three technologies: post-combustion, pre-combustion and oxyfuel. This requires that for each dedicated line different alternative options are introduced. Here, only one generic fossil fuelled plant and CO2 capture technology is modelled, as opposed to modelling all three individually. This is because the differences in costs between different capture technologies are minimal in comparison to the differences in cost between alternative energy options.

Network modelling

A further extension is to model different transport options. Broeck (2010) investigated different options for modelling a network approach in MARKAL, and found that in order to do this it was necessary to reduce the size of the model by clustering similar situations. Here, network modelling is not considered, as it provides little value added.

Stepwise cost for transport and storage

A simplified way to increase the level of detail in transport and storage representation is to add a stepwise cost. This can be applied so that for an increasing amount of CO2, the distance or depth has to be increased, and accordingly so do the costs.

5.3. GENERAL SCENARIO DESCRIPTION

The number of scenarios to be examined was limited in order to ensure that clear messages and relations could be drawn from the study, and to avoid too complex a picture where lessons are unable to be learnt. The emphasis of this analysis is on CCS application. Therefore, one demand side scenario for each region was developed ("reference demand"), as explained in sections 2.1.6 and 2.3.6, and several supply side scenarios. The demand scenario in each region takes into account expected improvements in demand side management in terms of expected increase of efficiency due to general improvement of equipment to be used in the future and deployment of some renewable options at demand side which could displace electricity in some cases (e.g. solar heating). In the case where a country decides to implement active energy efficiency policy, reduction of electricity demand is possible. Preliminary investigations yielded the view that these variations in demand scenario would result in a 5% decrease of consumption. On the supply side, the following scenarios were modeled: Reference scenario – this is BaU (Business as Usual) or "free"/"least cost" scenario. In other

words this scenario assumes more or less "normal" or "expected" development path in power generation without any constraining policies (assuming free market in electricity,


118

taking into account individual country/companies energy committed projects, security of supply issues and similar).

Baseline scenario – this scenario assumes the application of some decided policy actions (i.e. policies to be put in place as stated in government planning documents).

CO2 tax/price – in this scenario, an increase of CO2 value is assumed, monitoring which technologies will "trigger-in" and when CCS will become attractive. In MESSAGE, a CO2 price is modeled in the same way as a CO2 tax, and so the terms are interchangeable from a purely technical modeling standpoint, although both clearly entail different policy mechanisms.

CO2 limit – CO2 emissions from the power sector were explicitly limited across the region. This set of scenarios was combined with the CO2 price scenarios.

Forced CCS –quantitative target(s) for CCS penetration are fixed in terms of CCS technologies share in total electricity production.

Renewable energy sources (RES) – forced construction of renewables. This scenario is of interest due to initiatives to increase share of renewables in the electricity supply mix.

Different scenarios were compared to the reference scenario in terms of total system cost, investment in power plants, generation and capacity structure, electricity (generation) prices and CO2 emissions.

5.4. SIMULATION ASSUMPTIONS – BALKAN REGION

There are number of assumptions behind each particular scenario and there are number of general assumptions used across all scenarios. The general assumptions used in the Balkan region are: Planning horizon covers the period from 2015 until 2030. All costs are presented in US dollars. Uniform discount rate of 8% was used across the region. Nuclear programs – several jurisdictions are considering the development of nuclear power

plants and these considerations have been taken into account. The nuclear option is open after 2025 (the assumption is based on the idea that at least 15 years is needed from the positive decision on nuclear program development until the first commercial operational unit). The nuclear option is considered in Croatia, Albania and Macedonia. Specific investment cost in nuclear are assumed to be 4,190 USD/kW (3,000 EUR/kW). Scenarios without the nuclear option were also developed.

Availability of natural gas – natural gas for electricity generation is immediately (i.e. from 2015 as the first model year) available in Croatia, Serbia and Macedonia, while in other jurisdictions, gas was assumed to become available beyond 2020.

Coal import – for countries with undeveloped coal mining industries (due to low quality coal locations and/or low reserves) coal imports were assumed (i.e. for Croatia and Albania having direct sea access).

Interconnection transmission capacities between regions were modeled taking into account NTC (Net Transfer Capacity). NTC values were estimated based on Entso-e historical data71.

A gradual decrease of imports outside of the region was assumed, i.e. the region is gradually becoming independent in terms of electricity supply (transition period of ten years starting from 2015 was assumed in order to reach practically zero electricity imports). Trade between jurisdictions in the region was limited only by the capacity of interconnectors.

71

http://www.entsoe.eu


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External market electricity price was fixed at 84 USD/MWh (i.e. 60 EUR/MWh) for all scenarios. Simulations were based on a purely competitive market, meaning that local plants could compete for supply with surrounding systems (price on surrounding markets was fixed in advance and sales to external market permitted in line with available interconnection capacities).

Fuel prices are given in Table 106 and are assumed to be constant over the modeling horizon.

Table 48: Fuel prices used in simulation for Balkan region

Fuel Unit Price USD/GJ Price***

Fuel oil USD/ton 438 10.6

Natural gas UScent/m3 34.6 9.9

Coal - imported USD/ton 60.0 2.4

Coal – domestic* USD/ton 21.6 2.5

Nuclear fuel** USD/MWh 10.5 1.0 * - average price for most of the local coals; Only Kosovo has price at 1.4 USD/GJ ** - expressed per unit of produced electricity *** - all prices per unit of input fuel

5.5. CO2 STORAGE AND TRANSPORT IN BALKAN REGION

Based on the analysis of underground storage and transport options, and the associated costs in the Balkan area, the following table summarizes the volume and cost data related to CO2 storages and CO2 transport that were used in the model. The storage options are based on the reservoir matrix in Annex A. Where there is limited availability of data, higher storage and transportation costs were assumed, since CO2 either has to be exported and transported a larger distance or development of locally available storage is required, which is subject to uncertainty and therefore higher costs.


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Table 49: Data on CO2 storage volume, storage and transportation costs used in simulation for Balkan region

Jurisdiction Category

Storage type Storage

volume total Oil/gas

field Saline

aquifer Salt

dome

Albania

Storage volume [Mton CO2] 111 no data 20 131

Storage cost [USD/ton CO2] 7.5 10

Transport cost [USD/ton CO2] 4


Storage volume [Mton CO2] no data 197 no data 197

Storage cost [USD/ton CO2] 7.5

Transport cost [USD/ton CO2] 2.5

Croatia

Storage volume [Mton CO2] 148.5 351 no data 499.5

Storage cost [USD/ton CO2] 7.5 7.5


Kosovo

Storage volume [Mton CO2] no data no data no data 0

Storage cost [USD/ton CO2] 10


Macedonia

Storage volume [Mton CO2] no data 390 no data 390

Storage cost [USD/ton CO2] 7.5


Montenegro




Serbia




Region Storage volume [Mton CO2] 259.5 938 20 1 217.5

5.6. CANDIDATE POWER PLANTS IN BALKAN REGION

The following table reviews candidate power plants used in the techno-economic model. Some of the technologies were applied in a uniform way across the region, while jurisdiction specific projects are listed separately.


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Table 50: Power expansion candidates in Balkan region

Plant Fuel Capacity Efficiency Availability

Investment cost

Variable cost

Fixed cost

Earlieast available

Maximum installed

MW ratio ratio USD/kW USD/MWh USD/kW/yr Year MW

Region wide

CCS Coal coal 500 0.38 0.85 3 211 4.6 48.2 2020

CCS CCGT gas 300 0.47 0.85 1 611 2.8 27.7 2020

Coal coal 500 0.45 0.85 2 094 4.2 41.9 2016

CCGT gas 300 0.55 0.85 1 033 2.2 21.8 2015

OCGT gas 100 0.37 0.9 531 2.8 30.2 2015

Nuclear nucl 1000 0.33 0.92 4 189 7.0 27.9 2025

Albania

SHPP hydro 0.35 2 443 14.0 2015 100

Hydro hydro 0.424 2 737 14.0 2015 1000

Wind wind 0.254 2 094 2015 1300


Ugljevik 2 coal 400 0.42 0.85 2 094 3.2 27.9 2018

Gacko 2 coal 2x300 0.4 0.85 1 885 3.2 27.9 2018

Stanari coal 300 0.38 0.85 2 094 3.2 27.9 2015

Bugojno coal 2x300 0.42 0.85 2 234 3.2 27.9 2018

Kongora coal 2x250 0.38 0.85 2 304 3.2 27.9 2019

Tuzla coal 3x400 0.45 0.85 2 094 3.2 27.9 2018

Kakanj coal 400 0.45 0.85 2 094 3.2 27.9 2018

CCGT gas 150 0.5 0.85 1 257 4.0 20.9 2018 450

SHPP hydro 0.387 2 415 14.0 2015 280

Wind wind 0.25 2 094 2013 1200

Croatia

HPP hydro 2 500 0.48 3 491 14.0 2015 300

Wind wind 1 500 0.25 2 094 before 2015 1200

Kosovo

Zhur hydro 292 0.157 1 107 14.0 2016

Coal coal 500 0.46 0.85 2 094 4.8 27.9 2015 2000

Macedonia

Coal coal 300 0.4 0.85 1 536 6.6 27.9 2018

PSP Cebren hydro 333 0.288 1 419 14.0 2017

HPP hydro 0.373 2 737 14.0 2015 600

Wind wind 0.25 2 094 2015 600

Montenegro

Komarnica hydro 160 0.17 1 170 41.9 2018

Moraca hydro 238 0.33 2 928 14.0 2016

Wind wind 120 0.25 2 094 2015

Pljevlja coal 210 0.38 0.85 1 724 6.6 50.3 2015

Berane coal 100 0.36 0.85 2 482 6.6 67.0 2016

Serbia

Kolubara B coal 2x350 0.37 0.85 1 096 3.2 55.8 2015

TENT B3 coal 700 0.42 0.85 1 731 3.2 55.8 2016

SHPP hydro 0.3 2 792 14.0 2015 500

Wind wind 0.25 2 094 2015 1300

5.7. SCREENING CURVE ANALYSIS OF THERMAL POWER CANDIDATES IN BALKAN REGION

The screening curve analysis of major candidate power plants for expansion is illustrated by the following figures below. Total electricity generation costs are expressed as levelized generation cost for different plant capacity factors. Costs are estimated for different levels of carbon price (0, 25, 50 and 100 USD/ton CO2). For CCS options, costs for transport and storage were taken into


122

account, as well as the cost of purchasing permits at the CO2 price for the non-captured portion of the emissions (the CO2 capture rate is 85%). Screening curve analysis shows that in the case with no CO2 penalty, the most competitive option is conventional coal generation, followed by natural gas and nuclear power.

Figure 41: Screening curve analysis for Balkan region (carbon price 0 USD/ton CO2)

If a CO2 penalty of 25 USD/ton CO2 emitted is to be introduced, coal and nuclear options are almost equal, followed by gas. CCS still rests above these three options.


A further increase in carbon price to 50 USD/ton CO2 leaves nuclear as the most competitive option, while coal, coal with CCS and gas options are competing for second place.

50.0

100.0

150.0

200.0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Plant Capacity Factor

US

D/M

Wh

Gas CCS

Coal CCS

Gas

Nuclear

Coal

Expected range

of operation

50.0

100.0

150.0

200.0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1


US

D/M

Wh

Gas CCS

Coal CCS

Gas

Coal

Nuclear

Expected range

of operation


123


An increase in carbon fees up to 100 USD/ton CO2 leaves nuclear as it is, as the most competitive option, but the coal with CCS option takes the second place followed by gas with CCS and conventional gas and coal units.


5.8. SIMULATION RESULTS – BALKAN REGION

In this chapter, the results of the modeling analysis are presented for each scenario in Balkan region. The following outputs of the model are preseted: Structure of production capacity Structure of electricity generation Investment into new power plants Shadow prices i.e. marginal cost of electricity generation Total system costs (value of the objective function, i.e. total discounted cost of operation

and construction during planning horizon 2015-2030) CO2 emission (total and per kWh)

50.0

100.0

150.0

200.0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1


US

D/M

Wh

Gas CCS

Gas

Coal

Coal CCS

Nuclear

Expected range

of operation

50.0

100.0

150.0

200.0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1


US

D/M

Wh

Gas CCS

Gas

Coal

Coal CCS

Nuclear

Expected range

of operation


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5.8.1. REFERENCE (LEAST COST) SCENARIO

The Reference scenario assumes the least cost development plan, i.e. free construction of the most economic electricity generation options imposing only limits on earliest availability of some expansion options as discussed above, where no policies are applied. The main problem that power systems in Balkan region face today is the lack of local electricity production. At the beginning of the period under consideration the region is a net importer of electricity. Only Bosnia and Herzegovina exports electricity while other systems are either net importers or are close to being importers. There are very few large scale power projects under development and no major changes in electricity balance between local production and consumption can be expected before 2015. Therefore, with the expected increase in electricity consumption, electricity imports are also expected to increase until 2015. New power units are expected to go online in 2015/2016 at earliest. However, if plans for the development of local coal resources, especially in Serbia, Bosnia and Herzegovina and Kosovo are to be realized by 2020, there could be a complete reversal of the situation and the region could become a net electricity exporter. The following table and figure show the electricity generation structure for the Reference scenario.

Table 51: Electricity generation for the Reference scenario for Balkan region

TWh Hydro Wind Coal Gas Oil Nuclear Import-Export

Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.5 0.7 96.3 0.0 0.0 2.9 -17.6 113.8

2025 32.1 0.7 106.2 0.0 0.0 0.0 -9.2 129.8

2030 32.9 0.7 110.4 5.8 0.0 3.4 -6.3 146.9

Figure 45: Electricity generation for the Reference scenario for Balkan region

Electricity generation in the Reference scenario is dominated by coal, domestic and imported. Coal based generation increases its share in total electricity production from 49.1% during 2015 to 72.0% at the end of the planning horizon. In absolute values, coal based generation almost triples from 41.9 TWh in 2015 to 110.4 TWh in 2030. Hydro production also increases from 30.5 to 32.9 TWh, but decreases its share from 35.8% in 2015 to 21.5% during 2030. Production from natural gas and oil declines. Production from wind and other renewables (except hydro) remains

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand


125

the same, but with decreasing share in total production. Production from nuclear is increased in absolute value, but its share in total generation is decreased. The red line in the figure indicates total demand in the region. Surpluses of production (above the red line) are exported, starting from 2018. Difference between the red and yellow dotted lines shows total transmission and distribution losses in the system. New generation capacities installed in all jurisdictions from 2015 until 2030 reach approximately 16 GW. At the same time, total installed power increases from 19.1 GW to 27.1 GW to meet the overall rising demand. New installations are dominated by coal power plants, with a small increase in hydro and gas. After retirement of the existing unit at NPP Krško72, a new nuclear option is activated at the end of the planning period. Total investment into new power units amounts to 32.4 billion USD, while the total discounted cost of construction and operation are 32.1 billion USD.

Table 52: Installed generation power for the Reference scenario for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.9 1.1 0.1 0.3 25.5

2025 9.9 0.3 14.8 1.4 0.1 0.0 26.5

2030 10.3 0.3 14.9 1.2 0.0 0.4 27.1

Figure 46: Installed generation power fo the Reference scenario for Balkan region

Electricity prices (marginal or shadow prices)73 at the beginning of the period are high, reaching 111 USD/MWh. The reason for this is that there is limited electricity supply in the region. After new power units are commissioned in the region starting in 2016, marginal prices drop to a level of 74 USD/MWh and reach their minimum of 56 USD/MWh around year 2020. Beyond 2020, prices again increase as investments in new units are required in order to replace decommissioned capacity. In 2030, prices at the regional level reach 71 USD/MWh. The lowest marginal price at the end of the period was registered in Bosnia and Herzegovina, at 59 USD/MWh.

72

NPP Krško situated in Slovenia delivers 50% of energy and capacity to Croatia. Here decomissioning in 2023 was assumed (after 40 years of operation), but it is possible that unit will prolonge its operational life and continue operation after 2023. 73

Marginal price is the system price that has to be paid to satisfy an additional unit of demand.

19.1

22.2

22.6 2

4.1

24.3 2

5.5

25.1

25.1 25.8

25.7 26.5

27.0

27.2

27.5

27.5

27.1

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


126

Figure 47: Marginal system price for the Reference scenario for Balkan region

The increasing share of coal in the generation portfolio drives CO2 emission up, from 51.9 Mton in 2015 to 92.5 Mton in 2030, which is increase of 78% or by 40.6 Mton. Cumulative CO2 emissions over the period from all systems reaches 1,354.6 Mton. This is comparable to the estimated total underground storage volume in the region (bearing in mind that the potential volume in some jurisdictions is still to be determined and/or confirmed).

Figure 48: CO2 emissions from electricity production for the Reference scenario for Balkan region

The largest share in total regional CO2 emissions is from Serbia, which contributes on average 41.1%, followed by Bosnia and Herzegovina (22.9%) and Kosovo (13.6%).

40

60

80

100

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


127

Table 53: CO2 emissions from electricity production for the Reference scenario for Balkan region

Mton CO2 Croati

a Serbi

a

Bosnia and Herzegovin

a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.8 19.6 1.7 12.7 2.8 5.9 89.5

2025 10.0 33.3 23.1 0.0 15.6 5.5 4.2 91.8

2030 11.4 28.7 24.8 1.4 11.6 8.3 6.3 92.5

Total 2015-2030

123.8 551.0 314.0 19.2 185.9 72.6 88.2 1354.

6

Carbon intensity from electricity production is presented in the following figure, and increases from 0.6 kg CO2/kWh at the beginning of the period to 0.68 in 2020, and then gradually decreases to 0.6 by 2030. The reason for this increase at the beginning of the study period is in the increased share of production from coal during the first few years. Later in the time period, with gradual substitution of old coal fired units by new and more efficient units, carbon intensity decreases towards 2030.

Figure 49: Carbon intensity of electricity production for the Reference scenario for Balkan region

The construction of the new competitive power plants in the region leads to an increase of electricity exchange/trade across the area. The most competitive plants are lignite based plants in Serbia, Bosnia and Herzegovina and Kosovo. As expected, and as suggested by LCOE screening analysis in section 5.7, CCS is not a competitive option under Reference scenario (i.e. production costs of CCS plants are higher compared to other options).

Reference Scenario plus EOR

The EOR (Enhanced Oil Recovery) option was tested under the Reference scenario. EOR options means that the CO2 captured from power plants is injected into existing gas/oil wells in order to increase the amount of oil that can be recovered. In this way CO2 stored underground has additional benefit as revenues from oil/gas production could be increased. Based on the assumptions explained above, EOR could produce benefit of 40 USD/ton of CO2 stored. The EOR possibility was modeled only in Croatia and Albania, as a process that is only available from 2020 onwards, and simulation confirmed that in this case the coal with CCS option could be competitive without any additional policies (i.e. it is competitive in electricity markets).

0.60

0.62

0.64

0.66

0.68

0.70

2015 2020 2025 2030

kg

CO

2/k

Wh

kg CO2/kWh electricity produced


128

Total investment costs into new units increased to 41.0 billion USD, i.e. 8.6 billion USD above the Reference scenario. However, this substantial increase in investments is offset by the operational benefit, i.e. increased revenues from the crude oil market. Therefore total discounted system costs are actually lowered to 32.0 billion USD, i.e. 140 million USD below the Reference scenario amount. The share of CCS coal based generation in total electricity production reaches 13% in 2030 as presented in the figure below. Cumulative CO2 emission savings amount to 15.2 Mton, while total CO2 stored amounts to approximately 100 Mton by the end of the planning horizon in 2030. Figure 50 shows the share of electricity generation types in the electricity portfolio, categorized as non-CO2 emitting sources (e.g. renewable and nuclear) new build coal or gas plants with CCS, coal or gas plants retrofitted with CCS, and other. In this scenario there are no retrofits, but there new CCS units are constructed, as explained above. Figure 51 shows that CO2 is stored in Albania and Croatia, since this is where the EOR opportunities are.

Figure 50: Share of CCS based generation in the Reference EOR scenario for Balkan region

Figure 51: CO2 stored in the Reference EOR scenario for Balkan region

Other results for the Reference EOR scenario are given below.

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2

0.0

20.0

40.0

60.0

80.0

100.0

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


129

Table 54: Electricity generation for the Reference EOR scenario for Balkan region


Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.7 0.7 100.5 0.0 0.0 2.9 -21.9 113.8

2025 32.1 0.7 112.6 0.0 0.0 0.0 -15.6 129.8

2030 32.1 0.7 128.1 0.0 0.0 3.4 -17.4 146.9

Figure 52: Electricity generation for the Reference EOR scenario for Balkan region

Table 55: Installed generation power for the Reference EOR scenario for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 14.5 1.0 0.1 0.3 26.1

2025 9.9 0.3 15.7 1.4 0.1 0.0 27.5

2030 9.9 0.3 17.4 1.2 0.0 0.4 29.3

Figure 53: Installed generation power for the Reference EOR scenario for Balkan region

0

30

60

90

120

150

180

2015 2020 2025 2030

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

19.1

22.3

22.7

24.3

24.5

26.1

25.9

26.0 26.6

26.7 27.5 28.2

28.5

28.5

28.9

29.3

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


130

Figure 54: Marginal system price for the Reference EOR scenario for Balkan region

Figure 55: CO2 emissions from electricity production for the Reference EOR scenario for Balkan region

Table 56: CO2 emissions from electricity production for the Reference EOR scenario for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.8 20.1 1.7 12.7 3.1 7.0 91.4

2025 10.4 33.3 22.7 0.0 15.6 3.7 4.2 90.0

2030 11.4 28.7 24.8 0.0 11.6 9.7 3.8 90.0

Total 2015-2030 127.3 551.0 318.2 15.0 185.9 61.8 80.3

1 339.4

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


131

5.8.2. EFFICIENCY SCENARIO

The Efficiency scenario assumes that, due to an active government involvement in energy policy and different incentives, electricity demand can be decreased. Bottom-up analysis for two jurisdictions in the Balkan region showed that a decrease of 5% of final electricity demand could be expected on a 20-years time scale. This value of 5% was assumed to be achieveable over the whole region, and therefore applied across all countries. Final electricity demand for this scenario is presented in the table below. This scenario was run assuming no additional policies were applied – i.e. is the same as the Reference Scenario, except for a lower final demand.

Table 57: Final electricity demand in the Balkan region until 2030 for the Efficiency Scenario TWh 2010 2015 2020 2025 2030

Croatia 16.6 18.2 20.4 23.1 25.6

Bosnia and Herzegovina 11.3 12.8 14.9 16.8 18.5

Serbia 27.5 30.2 33.0 36.0 39.7

Montenegro 3.7 3.9 4.3 4.7 5.2

Kosovo 4.4 5.5 6.5 7.5 8.6

Albania 6.0 7.6 9.4 11.3 13.3

Macedonia 6.6 7.6 8.7 9.6 10.3

Total 76.1 85.8 97.1 109.0 121.2

Source: EIHP

The main consequences of increased efficiency are decreases in carbon emission and total system costs. Cumulative carbon emission savings during the analyzed period are 17.9 Mton CO2 compared to the Reference scenario. Total discounted costs are lowered by 1.12 billion USD74. Only 400 MW less capacity was installed than the Reference Scenario. Detailed results on the structure of electricity generation, installed capacity, carbon emission and marginal prices for the Efficiency Scenario are given below.

74

Objective function value in this case does not include additional costs caused by an active energy efficiency policy.


132

Table 58: Electricity generation for the Efficiency scenario for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.7 0.7 96.1 0.0 0.0 2.9 -19.4 111.9

2025 32.1 0.7 105.1 0.0 0.0 0.0 -12.4 125.5

2030 32.9 0.7 109.3 4.7 0.0 2.4 -10.5 139.6

Figure 56: Electricity generation for the Efficiency scenario for Balkan region

Table 59: Installed generation power for the Efficiency scenario for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.9 1.0 0.1 0.3 25.4

2025 9.9 0.3 14.7 1.3 0.1 0.0 26.3

2030 10.3 0.3 14.8 1.1 0.0 0.3 26.7

Figure 57: Installed generation power for the Efficiency scenario for Balkan region

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

19.1

22.3

22.7 2

4.1

24.2 2

5.4

25.0

24.8

25.4

25.5 26.3

26.6

26.6

26.6

27.0

26.7

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


133

Figure 58: Marginal system price for the Efficiency scenario for Balkan region

Figure 59: CO2 emissions from electricity production for the Efficiency scenario for Balkan region

Table 60: CO2 emissions from electricity production for the Efficiency scenario for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.8 19.6 1.7 12.7 2.8 5.7 89.3

2025 10.0 33.3 22.1 0.0 15.6 5.5 4.2 90.8

2030 11.0 28.7 23.8 1.4 11.6 8.3 6.3 91.2

Total 2015-2030 121.1 551.0 305.7 19.1 185.9 73.0 81.0

1 336.7

5.8.3. BASE LINE SCENARIO

The Base Line Scenario assumes that some of the power plant projects that are in the pipeline (albeit currently in different phases and with no final investment decision taken) will be completed

40

60

80

100

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


134

before 2020. In most cases these are hydro power plants projects (Croatia, Albania, Macedonia, Bosnia and Herzegovina and Montenegro) and some wind power plants. Also, construction of some thermal power plants was set to be forced by the model, but some of them were already selected as the competitive under the Reference (least cost) scenario anyway. Expressed in absolute numbers the Base Line Scenario assumes fixed construction of 4,560 MW by 2020, of which 1,600 MW is in hydro, 600 MW in wind, 1,800 MW in coal thermal plants and 550 MW in CCGT. The rest of the plants to be constructed are selected based on the least-cost criteria. The consequences of fixing construction of certain plants compared to the Reference scenario are summarized below:

The pattern of marginal prices during period changes slightly while the average level of marginal prices remains practically unchanged (see figure below).

CO2 emissions are slightly lower, leading to cumulative savings of 15.8 Mton or 1.2%. Total new installed capacity is increased to 18.4 GW or 2.4 GW above the Reference

scenario. Total installed capacity in 2030 reaches 29.5 GW. Due to higher installed capacity, total investment costs into new power plants are

increased to 34.0 billion USD. Total discounted system costs are increased to 33.5 billion USD or by 1.37 billion USD

above the Reference scenario. Detailed results for Base Line scenario are presented in the tables and figures below.

Table 61: Electricity generation for the Base Line scenario for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 35.9 2.0 94.6 0.0 0.0 2.9 -21.6 113.8

2025 36.3 2.0 104.5 0.0 0.0 0.0 -12.9 129.8

2030 37.1 2.0 109.1 7.9 0.0 3.4 -12.6 146.9

Figure 60: Electricity generation for the Base Line scenario for Balkan region

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand


135

Table 62: Installed generation power for the Base Line scenario for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.3 1.0 0.7 0.3 19.1

2020 11.3 0.9 13.7 1.5 0.1 0.3 27.9

2025 11.4 0.9 14.6 1.9 0.1 0.0 28.9

2030 11.7 0.9 14.7 1.7 0.0 0.4 29.5

Figure 61: Installed generation power for the Base Line scenario for Balkan region

Figure 62: Marginal system price for the Base Line scenario for Balkan region

19.1

23.8

24.3

26.7

26.6 2

7.9

27.5

27.5

28.1

28.1 28.9

29.3

29.5

29.2

29.8

29.5

0

5

10

15

20

25

30

35

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

40

60

80

100

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


136

Figure 63: CO2 emissions from electricity production for the Base Line scenario for Balkan region

Table 63: CO2 emissions from electricity production for the Base Line scenario for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.8 17.2 1.7 12.7 2.8 7.0 88.3

2025 10.0 33.3 21.4 0.0 15.6 5.6 4.2 90.2

2030 11.3 29.8 23.6 1.4 11.6 8.3 6.1 92.2

Total 2015-2030 120.4 557.9 292.7 18.5 185.9 74.5 88.9

1338.8

5.8.4. RNEWABLE ELECTRICITY SOURCES (RES POLICY) SCENARIO

The RES scenario assumes increased construction of renewable resources, including large hydro. The following table summarizes modeled forced construction of renewable energy sources based on governments' and electricity companies' plans/strategies and/or project-promotional publications. Increased construction of renewables as presented in the table will keep the share of renewables in total generation close to 30% by 2030 (compared to the 21.9% in the Reference scenario).

Table 64: Forced construction of renewables in the RES scenario for Balkan region

Jurisdiction HPP SHPP WIND Total

[MW]

HR 300 - 1,200 1,500

RS - 200 600 800

BA 500 160 400 1,060

MN 238 59 145 442

KO 292 - - 292

AL 600 100 500 1,200

MK 400 100 350 850

Total 2,330 619 3,195 6,144

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


137

Total installed power at the end of the period reaches 31.9 GW, while total new installed capacities amount to 20.8 GW. Due to forced installations, the generation of hydro and wind power plants increases substantially compared to the Reference scenario. As more energy is available locally, surpluses could be exported. Greater use of renewables leads to a decrease in CO2 emissions. Cumulative CO2 emissions in 2030 amount to 1,310.5 Mton, i.e. 44.1 Mton or 3.3% less compared to the Reference scenario. Marginal prices follow similar dynamics to the Reference scenario. Detailed results for RES scenario are presented in the tables and figures below.

Table 65: Electricity generation for theRES scenario for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.55 0.70 41.91 7.58 1.80 2.87 15.62 101.03

2020 38.48 6.14 92.89 0.00 0.00 2.87 -26.61 113.76

2025 39.01 6.97 103.37 0.00 0.00 0.00 -19.53 129.81

2030 39.85 6.97 108.06 4.75 0.00 3.44 -16.14 146.93

Figure 64: Electricity generation for the RES scenario for Balkan region

Table 66: Installed generation power for the RES scenario for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.3 1.0 0.7 0.3 19.1

2020 12.2 2.8 13.4 0.9 0.1 0.3 29.8

2025 12.3 3.2 14.4 1.3 0.1 0.0 31.3

2030 12.7 3.2 14.6 1.1 0.0 0.4 31.9

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand


138

Figure 65: Installed generation power for the RES scenario for Balkan region

Figure 66: Marginal system price for the RES scenario for Balkan region

19.1

23.9 2

5.1

27.5

28.0

29.8

29.7

29.6

30.1

30.5 31.3

31.7

31.6

31.7

32.2

31.9

0

5

10

15

20

25

30

35

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

40

60

80

100

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


139

Figure 67: CO2 emissions from electricity production for the RES scenario for Balkan region

Table 67: CO2 emissions from electricity production for the RES scenario for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.8 17.5 1.7 12.7 2.8 5.2 86.7

2025 10.0 33.3 20.5 0.0 15.6 5.5 4.2 89.1

2030 11.0 28.7 22.8 1.4 11.6 8.3 6.3 90.2

Total 2015-2030

120.3 551.0 285.4 18.8 185.9 72.0 77.0 1310.

5

5.8.5. CO2 PRICE SCENARIO

In the CO2 Price Scenario, a penalty on CO2 emissions from power generation was imposed. This can be interpreted either as a tax, such that for every ton of CO2 emitted, the emitting unit is penalized and must pay a penalty equal to the tax, or as a price, whereby an emitting unit must buy permits at that particular CO2 price for every ton emitted. These are modeled the same way in MESSAGE. Hereafter, the scenario refers to CO2 prices in order to be consistent. The system was tested for various levels of CO2 prices assuming a gradual increase of price as presented in the figure below.

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


140

Figure 68: Different levels of CO2 price used in the simulation

Table 68: Description of different cases simulated under the CO2 Price scenario for Balkan region

Scenario – CO2 Price

Case CO2 Price Note

Case 1

Gradual increase from zero in 2015 to 25 USD/ton CO2 in 2020 and constant beyond (Level 1 – see figure above)

Nuclear option active

Case 2

The same as for Case 1, i.e. gradual increase from zero in

2015 to 25 USD/ton CO2 in 2020 and constant beyond (Level 1 – see figure above)

No nuclear option

Case 3


No nuclear option

Case 4


No nuclear option

Case 1 The first case was to gradually increase the CO2 price from zero in 2015 to 25 USD/ton CO2 in 2020 and then to keep it constant until 2030. A level of 25 USD/ton CO2 corresponds to the current prices at European CO2 emission allowances market, which is relevant for the Balkan area. Outcome of Case 1: The CO2 price increases competitiveness of low or no CO2 emission technologies. As suggested by the screening curve analysis, a carbon price of 25 USD/ton CO2 has a strong influence on coal plants and brings nuclear units in direct competition with coal option. However, this level of carbon penalty is not enough for CCS to be deployed; i.e. CCS units are still more expensive compared to the other options.

0.0

25.0

50.0

75.0

100.0

2015 2020 2025 2030

US

D/ton C

O2

CO2 Price Level 3 - 100 USD/ton




141

The coal option is still attractive in some jurisdictions (e.g. Kosovo, Bosnia and Herzegovina and Serbia), while in some others an increase in carbon price makes the coal option less attractive (e.g. Montenegro, Macedonia). Shares of fuels are different compared to the Reference scenario. The most noticeable change is a decline of coal share and increased shares of nuclear and natural gas. At the end of the period, the nuclear option is exercised and its share is substantially higher in comparison to the Reference scenario. The hydro option becomes a little more attractive compared to the Reference scenario. Assuming the same import/export prices in the South Eastern Europe electricity market75 as in the Reference scenario, export of electricity is not attractive under a CO2 price regime. The total share of CO2-free76 emission technologies in electricity production decreases from 40% in 2015 to 37.9% in 2030 (compared to only 24.2% in the Reference scenario. This is a substantial absolute increase in generation from CO2-free emission technologies). At the same time the coal share increases from 49% to 58% (72% in the Reference scenario). The change in generation structure is closely followed by the change in CO2 emission pattern. Emissions increase from 51.2 Mton at the start to 75.4 Mton at the end of the period. However, C=cumulative savings in CO2 emissions amount to 172.8 Mton compared to the reference scenario. On average marginal prices are increased by 20% compared to the Reference case and reach 76 USD/MWh at the end of the period. Total discounted sysem costs are increased to 41.7 billion USD, i.e. 9.6 billion USD above Reference scenario, mainly due to the increased CO2 payments.

Table 69: Electricity generation for the CO2 Price scenario – Case 1 for Balkan region


Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 32.9 0.7 77.0 0.3 0.0 2.9 0.0 113.8

2025 33.9 0.7 93.0 1.9 0.0 0.3 0.0 129.8

2030 33.9 0.7 85.4 5.8 0.0 21.1 0.0 146.9

75

Generally, increase of CO2 carbon prices leads to an increase in wholesale electricity prices as additional costs of carbon are transferred from generators to customers. Assumption of the same price level is a conservative approach and puts stress on the competition of the local generation. 76

Nuclear, hydro, wind and other renewables.


142

Figure 69: Electricity generation for the CO2 Price scenario – Case 1 for Balkan region

Table 70: Installed generation power for the CO2 Price scenario – Case 1 for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.3 1.0 0.7 0.3 19.1

2020 10.3 0.3 11.3 1.0 0.1 0.3 23.4

2025 10.5 0.3 13.0 1.4 0.1 0.0 25.4

2030 10.5 0.3 11.5 1.2 0.0 2.6 26.2

Figure 70: Installed generation power for the CO2 Price scenario – Case 1 for Balkan region

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Import-Export

Gas

Oil

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

19.1

22.0 22.7

23.1

23.0

23.4

23.5

24.0 24.6

24.6 25.4

25.8

25.7

25.6

25.9

26.2

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


143

Figure 71: Marginal system price for the CO2 Price scenario – Case 1 for Balkan region

Figure 72: CO2 emissions from electricity production for the CO2 Price scenario – Case 1 for Balkan region

Table 71: CO2 emission from electricity production for the CO2 Price scenario – Case 1 for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.2 51.2

2020 5.0 33.9 12.7 1.7 12.7 2.8 5.2 73.9

2025 10.0 33.3 16.5 0.0 15.6 2.8 2.5 80.7

2030 11.4 28.7 15.9 0.0 11.6 2.8 4.9 75.4

Total 2015-2030 126.0 527.8 219.7 15.0 185.9 42.0 65.4

1 181.8

Case 2: In Case 2, the CO2 Price was kept at the same level as in Case 1 (i.e. 25 USD/ton), and assumes that the nuclear option will not be implemented (although some jurisdictions are considering nuclear programs, no country in the region has taken a decision on its development).

60

65

70

75

80

85

90

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


144

Outcome of Case 2: The main difference between cases 1 and 2 is visible at the end of the period. Without a nuclear option, shares of coal and natural gas increases. No CCS was deployed as it is still un-competitive at this CO2 price. Total cumulative savings in carbon emissions are 153.5 Mton CO2 or 11.3% compared to the Reference scenario. Total discounted costs are increased by 9.66 billion USD or 30% above Reference level. Due to the construction of coal units in Case 2, marginal prices at the end of the period are higher compared to the Case 1, in which nuclear units were constructed. Detailed results for the CO2 Price scenario – Case 2 are presented in the tables and figures below.

Table 72: Electricity generation for the CO2 Price scenario – Case 2 for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 32.9 0.7 77.3 0.0 0.0 2.9 0.0 113.8

2025 34.6 0.7 92.6 1.9 0.0 0.0 0.0 129.8

2030 36.5 0.7 100.6 9.2 0.0 0.0 0.0 146.9



2015 9.6 0.3 7.3 1.0 0.7 0.3 19.1

2020 10.3 0.3 11.4 1.0 0.1 0.3 23.4

2025 10.7 0.3 13.0 1.4 0.1 0.0 25.5

2030 11.2 0.3 13.6 1.6 0.0 0.0 26.7

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Import-Export

Gas

Oil

Nuclear

Coal

Wind

Hydro

Final Demand

Demand


145



19.1

22.1 22.9

23.1

23.0

23.4

23.5

24.0 24.6

24.6 25.5

26.0

25.8

25.9

26.3

26.7

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

60

65

70

75

80

85

90

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


146

Figure 76: CO2 emission from electricity production for the CO2 Price scenario – Case 2 for Balkan region

Table 74: CO2 emissions from electricity production for the CO2 Price scenario – Case 2 for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.2 51.2

2020 5.0 33.9 13.1 1.7 12.7 2.8 5.2 74.2

2025 10.0 33.3 16.2 0.0 15.6 2.8 2.3 80.3

2030 12.6 28.7 20.9 0.0 11.6 8.3 1.9 84.1

Total 2015-2030 128.1 528.4 232.1 15.0 185.9 51.8 59.8

1 201.1

Case 3: Case 3 has the same underlying assumptions as Case 2, while the carbon price was gradually increased from zero in 2015 to 50 USD/ton CO2 in 2020 and kept constant until 2030. Outcome of Case 3: As a consequence of an increased carbon price, CCS technology was deployed in coal power plants. The most competitive option was application of CCS in the Kosovo area, where CCS starts to becom competitive after 2020, while the CCS option in some other jurisdictions became competitive at the end of the period. Other changes in generation structure are increased use of hydro, wind and natural gas. Annual CO2 emissions stay below 70 Mton throughout the entire period. At the end of the period, 63 Mton of CO2 are stored underground, which is an average of storing 5.8 Mton annually (in the period 2020-2030).

0

20

40

60

80

100

2015 2020 2025 2030

Mto

n C

O2

HR RS

BA MN

KO AL

MK


147

Figure 77: CO2 stored in the CO2 Price scenario – Case 3 for Balkan region

Cumulative CO2 emissions savings are 305.7 Mton or 22% compared to the Reference scenario. Marginal prices reach 95 USD/MWh in 2020 and stay high until the end of the period. The lowest marginal price at the end of the period is recorded for the Kosovo area – below 90 USD/MWh. Total discounted costs are increased to 50.5 billion USD, i.e. 18% above the Reference scenario. The share of electricity generation from CCS equipped power units represents 10.2% of total electricity generation in 2030.

Figure 78: Share of CCS based generation in the CO2 Price scenario – Case 3 for Balkan region

Detailed results for scenario CO2 Price – Case 3 are presented in the tables and figures below.


2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 37.9 0.7 66.6 3.1 0.0 2.9 2.6 113.8

2025 43.4 0.8 78.6 7.1 0.0 0.0 0.0 129.8

2030 44.1 0.8 91.4 10.6 0.0 0.0 0.0 146.9

0

20

40

60

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

CCS

Non CO2


148



2015 9.6 0.3 7.3 1.0 0.7 0.3 19.1

2020 12.3 0.5 10.8 1.9 0.1 0.3 25.9

2025 14.1 0.5 11.3 3.1 0.1 0.0 29.0

2030 14.3 0.5 12.4 3.3 0.0 0.0 30.5


0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Import-Export

Gas

Oil

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

19.1

22.3 23.4

24.0

24.3 2

5.9 26.8

27.4

27.8

27.8 29.0

29.3

29.5

29.8

30.1

30.5

0

5

10

15

20

25

30

35

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


149



Table 77: CO2 emissions from electricity production for the CO2 Price scenario – Case 3 for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 4.9 33.9 3.3 0.0 12.9 3.2 5.0 63.2

2025 11.6 27.8 6.3 0.0 15.3 3.2 2.1 66.4

2030 12.9 28.9 8.8 0.0 13.1 3.6 0.7 68.1

Total 2015-2030 135.0 489.0 118.2 6.7 193.2 47.4 59.4

1048.9

Case 4: Case 4 assumes gradual increase of carbon price to 50 USD/ton CO2 by 2020 (i.e. as in Case 3) and then a further increase to 100 USD/ton CO2 by 2025.

70

75

80

85

90

95

100

105

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

10

20

30

40

50

60

70

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


150

Outcome of Case 4: Due to the high carbon price, CCS becomes much more competitive compared to the other scenarios and is deployed region-wide. The CCS retrofit option77 also becomes competitive. The share of hydro and wind is increased, and the share of natural gas is increased, but power generation is dominated by coal with CCS. A substantial drop in CO2 emissions is registered after 2020 (the earliest year in which CCS units or CCS retrofits could be put into operation). Cumulative savings in CO2 emission are 837.1 Mton. At the end of the period 650 Mton of CO2 is stored underground. Total electricity demand is increased from 2020 due to the large deployment of CCS retrofit option.

Figure 83: Share of CCS based generation in the CO2 Price scenario – Case 3 for Balkan region

Figure 84: CO2 stored in the CO2 Price scenario – Case 4 for Balkan region

Detailed results for the CO2 Price scenario – Case 4 are presented in tables and figures below.

77

The CCS retrofit option means retrofitting of some existing or future plants (mainly those to be constructed by 2020) with CCS. Retrofit options are more expensive compared to the pure CCS option, by 40%.

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2

0

100

200

300

400

500

600

700

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


151


2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 38.0 0.7 68.5 3.1 0.0 2.9 2.6 115.8

2025 43.8 1.9 85.8 7.4 0.0 0.0 0.0 138.9

2030 44.5 2.7 99.2 10.6 0.0 0.0 0.0 157.1



2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 11.9 0.3 11.1 1.0 0.1 0.3 24.8

2025 13.9 0.8 14.2 1.3 0.1 0.0 30.4

2030 14.2 1.2 13.6 1.5 0.0 0.0 30.5


0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Import-Export

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

19.1

21.9 22.6

22.8

23.2 2

4.8 2

6.1

29.0 30.0

29.7

30.4

31.0

31.1

30.3

30.6

30.5

0

5

10

15

20

25

30

35

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


152



Table 80: CO2 emission from electricity production for the CO2 Price scenario – Case 4 for Balkan region

Mton CO2 Croatia Serbia Bosnia and

Herzegovina Montenegro Kosovo Albania Macedonia Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 2.9 27.5 3.6 0.0 10.6 3.2 5.0 52.7

2025 1.9 3.7 1.1 0.6 2.6 1.5 0.1 11.5

2030 2.4 4.4 1.1 0.6 3.2 1.8 0.1 13.6

Total 2015-2030 50.2 227.6 64.3 13.9 89.5 31.2 40.8 517.6

70

80

90

100

110

120

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

20

40

60

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


153

5.8.6. THE CO2 LIMITED SCENARIO

In the CO2 Limited Scenario, several cases were tested, depending on an imposed CO2 emission limit and simultaneous application of the CO2 price. A description of simulated cases is given in the following table.

Table 81: Description of different cases simulated under the CO2 Limited scenario for Balkan region

Scenario – CO2 Limit

Case CO2 limit CO2 price

Case 1 -10% in 2030 compared to the

Reference scenario zero


Reference scenario NO nuclear option

zero


Reference scenario zero



zero


Reference scenario 25 USD/ton CO2 from 2020



25 USD/ton CO2 from 2020

Limits on CO2 emission were applied at the country level by comparing the emissions to the levels under the Reference scenario. The main conclusions from the simulation and optimization of the CO2 Limited set of cases are are summarized below: When the CO2 limit in 2030 is set at a 10% reduction compared to the Reference scenario,

CCS retrofits become competitive on a small scale at the end of the period in the Kosovo area, since it has the cheapest coal development options. The driving factor for this is the marginal cost of the CO2 limit, which passes 50 USD/ton CO2 at the end of the period in the Kosovo area. If the nuclear option is not included then CCS retrofits also become attractive in other jurisdictions (e.g. Croatia).

Similarly, if the CO2 limit is further strengthen to a 20% reduction by 2030 (compared to the Reference scenario), CCS retrofit becomes competitive in the Kosovo area and then in Croatia. The quantity of CO2 removed from the system is low if nuclear power is also available. If the nuclear option is not available, CCS options for coal units become competitive in the Kosovo area at the end of the period. In other jurisdictions CCS retrofits are used (Croatia, Macedonia).

For a CO2 limit set at a 20% reduction by 2030 compared to the Reference scenario and a CO2 price set at 25 USD/ton, the CCS retrofits become an option only at the end of the study period. If the nuclear option is excluded, CCS for coal units becomes competitive in Kosovo area after 2025, while CCS retrofits are used in Croatia.

Detailed results for each case are presented below.


154

Detailed results for the CO2 Limited scenario - Case 1

Table 82: Electricity generation for scenario CO2 Limited - Case 1 for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.5 0.7 90.7 0.0 0.0 2.9 -12.0 113.8

2025 32.1 0.7 97.0 0.0 0.0 0.0 0.0 129.8

2030 33.6 0.7 101.2 2.6 0.0 8.9 0.0 147.1

Figure 89: Electricity generation for the CO2 Limited scenario - Case 1 for Balkan region

Figure 90: Share of CCS based generation for the CO2 Limited scenario - Case 1 for Balkan region

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2


155

Table 83: Installed generation power for the CO2 Limited scenario - Case 1 for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.1 1.1 0.1 0.3 24.8

2025 9.9 0.3 13.7 1.4 0.1 0.0 25.4

2030 10.5 0.3 13.7 1.2 0.0 1.1 26.8

Figure 91: Installed generation power for the CO2 Limited scenario - Case 1 for Balkan region

Figure 92: Marginal system price for the CO2 Limited scenario - Case 1 for Balkan region

19.1

22.2

22.6 2

4.0

23.7 24.8

24.3

24.2

24.6

25.0

25.4 26.0

26.1

26.1

26.6

26.8

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


156

Figure 93: CO2 emissions from electricity production for the CO2 Limited scenario - Case 1 for Balkan region

Table 84: CO2 emissions from electricity production for the CO2 Limited scenario - Case 1 for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.1 17.2 1.7 12.0 2.8 5.2 85.0

2025 8.7 32.0 20.9 0.9 11.6 5.1 5.3 84.5

2030 10.3 25.9 22.3 1.3 10.5 7.5 5.6 83.3

Total 2015-2030 116.8 520.8 285.9 22.1 168.7 65.1 86.0

1265.4

0

20

40

60

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


157


Table 85: Electricity generation for the CO2 Limited scenario - Case 2 for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.5 0.7 90.7 0.0 0.0 2.9 -12.0 113.8

2025 32.7 0.7 96.4 0.0 0.0 0.0 0.0 129.8

2030 37.8 0.7 101.3 7.8 0.0 0.0 0.0 147.6



0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2


158


2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.1 1.1 0.1 0.3 24.8

2025 10.1 0.3 13.6 1.4 0.1 0.0 25.5

2030 11.8 0.3 13.7 1.6 0.0 0.0 27.4



19.1

22.2

22.6 2

4.0

23.7 24.8

24.3

24.2

24.6

25.0

25.5 26.3

26.3

26.7

27.2

27.4

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


159



Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 39.1 17.2 1.7 12.0 2.8 5.2 85.0

2025 8.7 32.0 20.9 0.5 11.6 5.1 5.0 83.8

2030 10.3 25.9 22.3 1.3 10.5 7.5 5.6 83.3

Total 2015-2030 116.8 520.8 285.9 21.7 168.7 65.1 85.0

1264.0

0

20

40

60

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


160



2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.5 0.7 89.5 0.0 0.0 2.9 -10.8 113.8

2025 33.2 0.7 92.7 1.9 0.0 1.3 0.0 129.8

2030 35.9 0.7 89.7 4.9 0.0 16.1 0.0 147.3



0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2


161


2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.0 1.1 0.1 0.3 24.6

2025 10.3 0.3 13.1 1.4 0.1 0.2 25.4

2030 11.1 0.3 12.2 1.2 0.0 2.0 26.8



19.1

22.2

22.6 2

4.0

23.7 24.6

24.3

24.3

24.6

25.2

25.4 26.1

26.3

26.1

26.6

26.8

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


162



Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 38.5 17.2 1.7 11.7 2.8 5.2 84.1

2025 8.1 31.4 19.7 1.2 11.0 4.7 5.5 81.5

2030 9.1 23.0 19.8 1.1 9.3 6.7 5.0 74.0

Total 2015-2030 111.9 505.6 277.4 22.8 161.6 61.0 83.6

1 224.0

0

20

40

60

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


163



2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 31.5 0.7 89.5 0.0 0.0 2.9 -10.8 113.8

2025 34.6 0.7 92.7 1.9 0.0 0.0 0.0 129.8

2030 40.0 0.7 98.6 9.2 0.0 0.0 0.0 148.4



0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2


164


2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.0 1.1 0.1 0.3 24.6

2025 10.8 0.3 13.1 1.4 0.1 0.0 25.7

2030 12.5 0.3 13.4 1.6 0.0 0.0 27.8



19.1

22.2

22.6 2

4.0

23.7 24.6

24.3

24.2

24.6 25.3

25.7

26.2

26.4

26.6 27.4

27.8

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


165



Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 7.1 38.5 17.2 1.7 11.7 2.8 5.2 84.1

2025 8.1 31.4 19.7 1.2 11.0 4.7 5.4 81.5

2030 9.1 23.0 19.8 1.1 9.3 6.7 5.0 74.0

Total 2015-2030 111.7 505.6 276.8 23.1 161.6 61.0 83.5

1 223.5

0

10

20

30

40

50

60

70

80

90

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


166



2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 32.9 0.7 77.3 0.0 0.0 2.9 0.0 113.8

2025 35.0 0.7 84.6 0.0 0.0 9.5 0.0 129.8

2030 36.5 0.7 82.7 3.5 0.0 23.6 0.0 147.0



0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Import-Export

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2


167


2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 10.3 0.3 11.4 1.0 0.1 0.3 23.4

2025 10.8 0.3 12.0 1.4 0.1 1.2 25.8

2030 11.2 0.3 11.2 1.2 0.0 2.9 26.8



19.1

22.3 23.0

23.1

23.2

23.4

23.8

24.3

24.8

24.7 2

5.8

26.3

26.3

26.3

26.4

26.8

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


168



Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 5.0 33.9 14.3 1.7 11.7 2.8 5.2 74.4

2025 8.1 30.0 19.6 0.0 11.0 3.2 5.3 77.1

2030 9.1 23.0 19.8 0.0 9.3 6.5 5.0 72.8

Total 2015-2030 110.6 483.5 254.8 14.7 161.3 52.2 79.8

1156.9

0

10

20

30

40

50

60

70

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


169

Detailed results for scenario CO2 Limited - Case 6


2015 30.6 0.7 41.9 7.6 1.8 2.9 15.6 101.0

2020 33.1 0.7 77.0 0.0 0.0 2.9 0.0 113.8

2025 37.1 0.7 88.6 3.6 0.0 0.0 0.0 129.9

2030 41.4 0.7 96.4 9.9 0.0 0.0 0.0 148.3



0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Import-Export

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2


170


2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 10.3 0.3 11.4 1.0 0.1 0.3 23.5

2025 11.5 0.3 12.5 1.4 0.1 0.0 25.9

2030 12.9 0.3 13.1 1.6 0.0 0.0 27.9



19.1

22.3 23.0

23.1

23.1

23.5

23.9

24.4 25.0

25.2 25.9

26.4

26.5

26.9 27.5

27.9

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE


171



Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.5 22.6 10.3 1.7 5.7 0.4 5.8 51.9

2020 5.0 33.9 14.3 1.4 11.7 2.8 5.2 74.2

2025 8.1 30.0 19.7 0.0 11.0 4.7 4.9 78.3

2030 9.1 23.0 19.8 1.1 9.3 6.7 5.0 74.0

Total 2015-2030 110.3 484.6 261.7 16.6 161.6 59.5 80.5

1 174.9

5.8.7. CCS TARGET SCENARIO

The main intention of the CCS Target scenario is an assessment of the impact of the specific policies for the targeted development of several CCS projects in the region (examining the impact on overall system cost and prices). In the CCS Target scenario, the deployment of a certain number of CCS units was fixed. The basis for fixed deployment of CCS technologies was the Reference scenario. The optimal solution from the least cost scenario was noted, and the CCS Target Scenario involved fixing the construction of CCS units starting from 2025, that would replace the conventional coal units that the Reference scenario called for the construction of (i.e. the total construction remains practically the same). In total, three CCS units were fixed – one unit in Kosovo, Serbia and Bosnia and Herzegovina (i.e. in jurisdictions with a significant amount of local coal available). This modification resulted in 7% share of CCS units in total production by 2030.

0

10

20

30

40

50

60

70

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


172

Figure 119: Share of CCS based generation in the CCS Target scenario for Balkan region

Cumulative carbon savings amount to 37 Mton of CO2, i.e. 2.7% less compared to the Reference scenario. At the same time the total discounted costs are increased by only 1.5%. In total, 42.7 Mton of carbon dioxide is stored underground by 2030.

Figure 120: CO2 stored in the CCS Target scenario for Balkan region

Detailed results for the CCS Target scenario are presented below.

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

2015 2020 2025 2030

TW

h

Other

RETROFIT

CCS

Non CO2

0.0

10.0

20.0

30.0

40.0

50.0

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


173

Table 100: Electricity generation for the CCS Target scenario for Balkan region TWh Hydro Wind Coal Gas Oil Nuclear Import-Export Demand

2015 30.55 0.70 41.91 7.58 1.80 2.87 15.62 101.03

2020 31.45 0.70 96.23 0.00 0.00 2.87 -17.49 113.76

2025 32.09 0.70 106.10 0.00 0.00 0.00 -9.08 129.81

2030 32.93 0.70 109.98 5.79 0.00 3.44 -5.92 146.93

Figure 121: Electricity generation for the CCS Target scenario for Balkan region

Table 101: Installed generation power for the CCS Target scenario for Balkan region GW Hydro Wind Coal Gas Oil Nuclear Total

2015 9.6 0.3 7.0 1.0 1.0 0.3 19.1

2020 9.8 0.3 13.9 1.1 0.1 0.3 25.5

2025 9.9 0.3 14.8 1.4 0.1 0.0 26.6

2030 10.3 0.3 14.9 1.2 0.0 0.4 27.1

Figure 122: Installed generation power for the CCS Target scenario for Balkan region

0

40

80

120

160

2015 2020 2025 2030

Years

TW

h

ENS

Oil

Gas

Nuclear

Coal

Wind

Hydro

Final Demand

Demand

19.1

22.2

22.6 2

4.0

24.3 2

5.5

25.0

25.1 25.8

25.7 26.6

27.0

27.3

27.6

27.5

27.1

0

5

10

15

20

25

30

2015 2020 2025 2030

GW

Oil

Nuclear

Gas

Coal

Wind

Hydro

Total


174

Figure 123: Marginal system price for the CCS Target scenario for Balkan region

Figure 124: CO2 emission from electricity production for the CCS Target scenario for Balkan region

Table 102: CO2 emission from electricity production for the CCS Target scenario for Balkan region

Mton CO2 Croati

a Serbi

a


a

Montenegro

Kosovo

Albania

Macedonia

Total

2015 5.47 22.55 10.27 1.67 5.70 0.41 5.83 51.9

2020 7.06 39.84 19.56 1.67 12.70 2.77 5.82 89.4

2025 9.98 33.34 22.77 0.00 13.20 5.62 4.20 89.1

2030 11.41 26.27 22.27 1.40 9.23 8.32 6.27 85.2

Total 2015-2030

124.0 538.6 303.4 19.2 171.4 72.8 88.1 1 317.6

5.9. COMPARISON OF SCENARIOS FOR BALKAN REGION

50

60

70

80

90

100

110

2015 2020 2025 2030

US

D/M

Wh

HR

RS

BA

MN

KO

AL

MK

SEE

0

20

40

60

80

2015 2020 2025 2030

Mto

n C

O2

MK

AL

KO

MN

BA

RS

HR


175

This chapter summarizes and compares the results across the different scenarios presented above. The following results are compared: Total discounted costs; Average generation costs; Marginal prices; CO2 emissions and emission savings; Volume of CO2 stored at the end of the period; Share of CCS generation in 2030 (CCS units and CCS retrofit together).

The three tables below summarize the main results for all scenarios/cases presented above. All differences are calculated related to the Reference scenario.

Table 103: Comparison of results across scenarios for Balkan region – Part I

Unit Category Scenario

Reference EOR Base Line RES Efficiency Target CCS

billion USD2010 Objective function value 32.1 32.0 33.5 34.7 31.0 32.6

billion USD2010 Difference - -0.14 1.37 2.52 -1.11 0.47

% Difference - -0.43 4.27 7.86 -3.47 1.47

Mton Cumulative CO2 emissions 1 354.6 1 339.4 1 338.8 1 310.5 1 336.7 1 317.6

Mton Difference - -15.2 -15.8 -44.1 -17.9 -37.0

% Difference - -1.1 -1.2 -3.3 -1.3 -2.7

Mton CO2 stored - 97.4 42.7

Mton CO2 retrofitted - - - - - -

% CCS share in 2030a - 12.9 - - - 6.9

GW New installation 16.0 18.19 18.44 20.84 15.62 16.1

GW Difference - 2.15 2.40 4.80 -0.41 0.1

GW Total installed 27.11 29.3 29.51 31.9 26.70 27.1

GW Difference - 2.15 2.40 4.80 -0.41 0.03

billion USD2010 Investment new plantsb 32.4 41.0 34.0 38.1 31.4 34.0

billion USD2010 Difference - 8.6 1.6 5.7 -1.0 1.7 a – CCS units and CCS retrofit together

b – without CCS retrofit


176

Table 104: Comparison of results across scenarios for Balkan region – Part II

Unit Category

Scenario - CO2 Price

25USD/ton 25USD/ton NO NUCL

50USD/ton NO NUCL

100USD/ton NO NUCL

billion USD2010 Objective function value 41.7 41.8 50.5 53.4

billion USD2010 Difference 9.60 9.66 18.42 21.27

% Difference 29.87 30.07 57.32 66.19

Mton Cumulative CO2 emissions 1 181.8 1 201.1 1 048.9 517.6

Mton Difference -172.8 -153.5 -305.7 -837.1

% Difference -12.8 -11.3 -22.6 -61.8

Mton CO2 stored - - 63.3 651.9

Mton CO2 retrofitted - - - 298.0

% CCS share in 2030a - - 10.2 69.5

GW New installation 15.1 15.65 19.5 19.4

GW Difference -0.94 -0.39 3.42 3.36

GW Total installed 26.18 26.72 30.5 30.5

GW Difference -0.94 -0.39 3.42 3.36

billion USD2010 Investment new plantsb 26.5 28.1 28.3 39.1

billion USD2010 Difference -5.9 -4.3 -4.1 6.8 a – CCS units and CCS retrofit together


Table 105: Comparison of results across scenarios for Balkan region – Part III

Unit Category

Scenario – CO2 Limit

-10% -10%,

NO NUCL -20%

-20%, NO NUCL

-20% 25USD/ton

-20% 25USD/ton NO NUCL

billion USD2010 Objective function value 32.5 32.6 32.8 33.0 42.0 42.2

billion USD2010 Difference 0.36 0.43 0.66 0.85 9.84 10.09

% Difference 1.12 1.34 2.06 2.64 30.61 31.41

Mton Cumulative CO2 emissions 1 265.4 1 264.0 1 224.0 1 223.5 1 156.9 1 174.9

Mton Difference -89.2 -90.6 -130.6 -131.2 -197.8 -179.7

% Difference -6.6 -6.7 -9.6 -9.7 -14.6 -13.3

Mton CO2 stored 0.7 4.5 1.5 28.8 0.3 24.7

Mton CO2 retrofitted 0.7 4.5 1.5 15.6 0.3 15.6

% CCS share in 2030a 0.5 2.8 1.2 10.9 0.4 5.8

GW New installation 15.7 16.3 15.7 16.7 15.8 16.83

GW Difference -0.35 0.30 -0.32 0.69 -0.28 0.80

GW Total installed 26.8 27.4 26.8 27.8 26.8 27.9

GW Difference -0.35 0.30 -0.32 0.69 -0.28 0.80

billion USD2010 Investment new plantsb 32.1 28.4 28.9 28.9 27.0 27.9

billion USD2010 Difference -0.3 -4.0 -3.5 -3.5 -5.4 -4.5 a – CCS units and CCS retrofit together



177

Figure 125: Comparison of total discounted costs across scenarios for Balkan region

32.13 31.9933.50

34.65

31.02

41.73 41.79

50.55

53.40

32.49 32.56 32.79 32.98

41.97 42.22

32.60

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10%

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Tax

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Bil

lio

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SD

2010


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Figure 126: Comparison of the marginal system price across scenarios for Balkan region

40.0

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US

D/M

Wh

Reference

Base Line

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Efficiency

CO2 Tax, 25USD/ton




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NUCL

Targeted CCS


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Figure 127: Comparison of average generation costs across scenarios for Balkan region

30.0

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2015 2020 2025 2030

US

D/M

Wh

Reference

Base Line

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Efficiency

CO2 Tax, 25USD/ton




CO2 Limit -10%


CO2 Limit -20%



CO2 Limit -20%, CO2 Tax 25USD/ton, NO NUCL

Targeted CCS


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Figure 128: Comparison of total CO2 emissions across scenarios for Balkan region

0.0

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120.0

2015 2020 2025 2030

Mto

n C

O2

Reference

Base Line

RES

Efficiency

CO2 Tax, 25USD/ton




CO2 Limit -10%


CO2 Limit -20%




NUCL

Targeted CCS


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Figure 129: Cumulative CO2 emissions savings across scenarios for Balkan region

1644

18

173154

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837

89 91131 131

198180

37

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10%

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Cu

mu

lati

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avin

gs [

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O2]


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5.10. CONCLUSIONS FOR BALKAN REGION

The current state of power systems in Balkan region For the purposes of this report, the Balkan region refers to the South Eastern European area covering Croatia, Bosnia and Herzegovina, Serbia, Kosovo, Montenegro, Albania and Macedonia. The main characteristics of power systems in Balkan region are:

The region as a whole is net importer of electricity. Only Bosnia and Herzegovina is a net exporter of electricity.

Electricity generation is mainly based on local coal resources (lignite and brown) and hydro.

Thermal power plants are old and operate at low efficiency levels. A large number of units will reach their operational life-time by around 2020. In the last 20 years only 2 new thermal units with installed power greater then 200 MW were constructed.

The transmission network is well developed and there are numerous of interconnections. Between national power systems there are no major transmission issues, but some internal (at the jurisdiction level) congestion negatively influences possible exchanges of electricity, driving wholesale electricity prices up in some cases. Submarine HVDC interconnection to Italy is under consideration (from Montenegro, Croatia and Albania). This would allow the development of large scale local coal production and the sale of electricity to the Italian market (with higher prices compared to the Balkan region) and could have a major impact on local electricity markets.

Electricity trade is mainly bilateral, i.e. there is no spot market (power exchange) to set up a benchmark for wholesale prices.

Electricity prices for final consumers are low and leave little incentives for investments into new generation facilities.

There is significant potential for the development of coal (Kosovo, Bosnia and Herzegovina, Serbia), hydro and wind.

Natural gas for electricity production is used in Croatia, and to a lesser extent in Serbia and Macedonia. There are plans for the whole region to use gas for electricity production. Gas is mainly imported from Russia, with only Croatia having its own production which covers part of the total domestic gas demand.

Several jurisdictions are considering introducing nuclear programs (Croatia, Albania, Macedonia).

Final electricity demand is estimated to increase by 50 TWh over the next 20 years. Increased needs will require the construction of new power plants.

Jurisdictions are members of the Energy Community, a regional organization under a binding agreement on gradual harmonization of energy legislation with the European Union. The Energy Community is supported by and closely related to the European Commission. The harmonization process is also preparation in part the accession process to the EU. Jurisdictions under consideration state EU accession as one of their main political targets. Croatia is expected to join the EU at the earliest in 2013, while other jurisdictions are expected to become EU members by 2020.

Croatia has quantified targets for CO2 emission reductions during the Kyoto period (2008-2012). Other jurisdictions (except Kosovo) have signed and ratified the UNFCCC and Kyoto protocol but do not have an obligation to reduce emissions. However, future international agreements on climate change and accession to EU could impose certain CO2 targets for the jurisdictions under consideration.


183

Summary of study Use of conventional fossil fuel technologies to cover increasing electricity needs in the future will inevitably lead to significant increases in CO2 emissions. An analysis of the possible use of CCS (carbon capture and storage) technology and its competitiveness to alternatives was carried out. The analysis consisted of three main parts: assessment of available underground storage volume in the region and the associated storage costs, assessment of transportation options and costs, and an assessment of technological options for CCS equipped coal and gas power plants including CCS as a retrofit option. At present, underground storage potential in Balkan region is estimated to be 1,257 Mton CO2. For the most part this is in deep saline aquifers (948 Mton) and the rest is in oil/gas fields and salt domes. The total volume is comparable to the cumulative CO2 emissions during 2015-2030 period under the Reference scenario. Estimation of storage volume was based on previous studies under the EU FP6 GeoCapacity project and publicly available data. In some countries, data was not available, or of low quality. More in-field research work is needed for a more reliable assessment of storage potential. Cost ranges for storing CO2 were estimated for different storage types. Transport of CO2 is technologically possible and cost estimates are reliable. The main influencing compontent taken account of in this study is the distance from the power plant to the storage site. Distances up to 250 km could be crossed without additional compressing stations. At present, there is no large-scale CCS power plant in commercial operation. Cost estimates can be made however, and it is expected that CCS will be commercially available some time beyond 2020. The main impacts of carbon capture in terms of power plant operation are increased internal consumption of energy at the plant, resulting decreased overall efficiency and increased investment and operational costs. The final result is increased generation cost. The period considered in the study was 2015-2030. A techno-economic model based on linear programming was developed and power systems were modeled as interconnected national systems. All costs were discounted to 2010 using a uniform discount rate of 8%. CCS competitiveness A screening curve analysis found that in the case with no CO2 emissions price, the most competitive energy generation option is conventional coal generation, followed by natural gas and nuclear. If a CO2 price of 25 USD/ton CO2 emitted is introduced, coal and nuclear options are almost equal, followed by gas. CCS still has a higher cost than these three options. A further increase of carbon price to 50 USD/ton CO2 leaves nuclear as the most competitive, while coal, coal with CCS and gas options compete for second place. An increase of carbon price to 100 USD/ton CO2 leaves nuclear as it is as the most cost effective technology choice, but coal with CCS takes second place, followed by gas with CCS and conventional gas and coal units. For the purposes of a system-wide analysis of the competitiveness of CCS, the following scenarios were simulated: Reference – least cost scenario with free competition between technologies. Base line – some projects currently under preparation were fixed and assumed to be

operational by 2020. RES – strong development of renewables (hydro and wind). Efficiency – lower final electricity demand due to an active energy efficiency policy. CO2 Price – introduction of different levels of CO2 price.


184

CO2 Limited – introduction of different CO2 emission reduction. Targeted CCS – targeted (fixed) development of CCS by 2030.

The reference scenario is dominated by coal based electricity generation. The generation structure changes as coal has the largest share of 73%, followed by hydro with 22%, with the remainder from gas and nuclear. Emissions increase from 52.7 Mton in 2015 to 91.9 Mton in 2030, i.e. by 75%. Cumulative CO2 emissions during the 2015-2030 period reach approximately 1355 Mton. Marginal system prices at the beginning of the period are high (111 USD/MW). The period from 2015 until 2020 is one of intensive construction of new power units. Marginal prices reduce to 56 USD/MWh as coal based electricity becomes available. Investment in replacement coal units continues after 2020 and marginal prices increase slightly toward the end of the period at 70 USD/MWh. Average generation prices increase from approximately 40 USD/MWh in 2015 to 50 USD/MWh in 2030. Under the Reference Scenario, CCS options are not competitive as they are more expensive than the alternatives available. Using the same set of assumptions as in the Reference scenario, an option for EOR (Enhanced Oil Recovery) was added and simulated, showing that CCS could be competitive without any further policies – i.e. it is competitive if coupled with oil/gas extraction. The EOR option assumed that the injection of CO2 into existing oil/gas fields could yield a benefit of 40 USD/ton of CO2 injected. Under assumptions that EOR is available, it is possible, at the same time, to reduce CO2 emissions by 1.1% compared to the Reference scenario, but increase total production (surpluses were exported to surrounding systems). Base line, Efficiency and Renewables scenarios were used to compare the influence of different policies on total costs, CO2 emissions and electricity prices. Under these scenarios CCS options were not competitive, but certain carbon emission savings could be achieved, assuming, for example, increased efficiency at demand side or intensive development of renewables, depending on the scenario. At the same time, average generation prices are higher compared to the Reference Scenario. The group of cases simulated under the CO2 Price scenario showed that CCS options become competitive when the CO2 price reaches approximately 50 USD/ton and assuming that the nuclear option is not available. CCS options were most competitive in the Kosovo area due to the low cost of coal development (favorable extraction conditions). The CCS share in total production in 2030 reaches 10.2%. At the same time alternatives like hydro and wind increase their share in total generation. Cumulative CO2 emissions are decreased by 22% compared to the Reference scenario (a large relative decrease due to a decrease of electricity exports – i.e. decrease of electricity production). By the end of the planning horizon approximately 63 Mton of CO2 is stored underground. Average generation costs at the end of the period are increased by almost 50% compared to the Reference scenario. Similarly, marginal prices are on average increased by 40%. An increase in the CO2 price to 100 USD/ton (without the nuclear option) leads to region-wide application of CCS options, including the retrofit of existing and/or new conventional coal and gas units (i.e. units constructed between today and 2020). At the end of the period practically all plants are equipped with CCS. Cumulative emissions drop sharply and are 62% (or 837 Mton) below the Reference scenario level. At the end of the period 650 Mton of CO2 is stored underground, out of


185

which 300 Mton is from CCS retrofitted plants. High carbon prices are followed by a further increase in average generation costs which are now more than 60% higher, compared to the Reference scenario. Marginal prices are on average increased by 47%. Under the CO2 Limited scenario, several carbon emission reduction cases were simulated, as well as their combination with carbon prices. CO2 reduction targets were introduced at each jurisdiction level relative to the emission levels from the Reference scenario. Simulations indicate that the CCS retrofit option already becomes attractive at the end of the study period for low reduction targets (10% reduction) and assuming that the nuclear option is not available. At higher reduction levels (20% reduction) new CCS units become competitive, also assuming the nuclear option is not available. While average generation costs remain at a level similar to the Reference scenario, marginal prices are increased between 4 and 23%, depending on the reduction target and other assumptions (e.g. availability of nuclear option, carbon price etc.). The Targeted CCS scenario was developed based on the Reference scenario (least-cost plan). Three 500 MW CCS coal units were added to the system around 2025, replacing conventional coal units in the jurisdictions with large coal reserves (Kosovo, Bosnia and Herzegovina and Serbia). This strategy led to a 7% share of CCS in total electricity production by the end of the period. Average generation costs are increased by 6%. The overall conclusion on the competitiveness of CCS in the Balkan area is that CCS technologies will compete in the market with nuclear power and that their maturity and fast commercialization will be key to whether the technology is deployed at scale. If CCS is combined with EOR this could substantially change the picture and make CCS an attractive and strongly competitive option without further policies. Targeted development of a certain number of CCS projects would require relatively large investments but have a mild influence on generation costs and could promote CCS and open the space for faster deployment. The most competitive CCS options are coal based CCS units in the Kosovo area due to the low coal cost there. At the same time, additional research and field work is needed to verify the existence and suitability of underground formations for long-term storage of carbon dioxide.


186

5.11 SCENARIO DESCRIPTION – SOUTHERN AFRICAN REGION

As in the case for the Balkan region, the number of scenarios presented was limited in order to keep the analysis focused and to allow lessons to be drawn. The scenarios were also tailored specifically to the region, and only those particularly relevant to the area were modeled. The following scenarios were modeled:

A Reference scenario: Similarly for the Balkan region, this scenario portrays the situation as it currently is and extrapolates it for the next twenty years without any additional policies. The resulting power sector is based purely on minimizing total system costs.

A Baseline scenario: This scenario portrays the situation where capacity expansion options go ahead according to plans and policies in place. The Integrated Resource Plan (IRP) for South Africa was modeled for this case, which includes a CO2 constraint. Two instances of this scenario were run:

o One without EOR and ECBM options included o One with EOR, ECBM options included

A CO2 price case (with a CO2 constraint for South Africa). Three different three different price levels were applied to the system with EOR and ECBM options included:

o 25 USD/ton CO278

o 50 USD/ton CO2 o 100 USD/ton CO2

5.12 GENERAL MODELING ASSUMPTIONS – SOUTHERN AFRICAN REGION

There are a number of general assumptions that apply to all scenarios. The main general assumptions for the Southern African region are:

The planning horizon is from 2010 to 2030.

All costs are in constant 2010 USD.

The overall real discount rate is 8%.

Coal and gas is available in all regions.

Nuclear power is only available in South Africa.

Wind power is only available in South Africa and Namibia.

Biomass is only available in South Africa and Mozambique.

Electricity imports by individual countries are constrained to 15% by 2020.

Electricity from intermittent renewables can only make up to 30% of total electricity generated.

Existing and future transmission lines are as per described in section 2.3.5.

Fuel prices are given in Table 106 and are assumed to be constant over the modeling horizon.

78

The 25 USD/ton CO2 is based on the current figure of about ZAR200/ton CO2 tax that is being discussed in South Africa.


187

Table 106: Fuel price assumptions for Southern African region

Fuel USD/GJ

Price

Diesel – imported 27.0

Natural gas – domestic 8.8

Natural gas – imported 10.8

Coal – domestic 2.0

Nuclear fuel 0.8

5.13 CO2 CAPTURE, STORAGES AND TRANSPORT IN THE SOUTHERN AFRICAN REGION

Table 107 shows the capture technologies and the parameters that were used to characterize them in the model. The cost parameters were calculated based on the South African IRP 2011 costs. The Southern African CCS plants costs are the SA IRP 2011 costs for a plant without CCS scaled by the ratio of the generic costs of plants with CCS to the generic costs of plants without CCS, as given in Table 45. The loss of efficiency from CCS due to the parasitic load was also calculated using the data in Table 45.

Table 107: Capture technologies, options and parameters for the Southern African region

Plant description Fuel Type Capital

cost USD/kW

Fixed O&M USD/kW

Variable O&M

USD/MWh Efficiency

Available capacity

factor

CCGT with CCS Gas 1,314 25.4 0.0 39% 89%

Coal Supercritical with CCS Coal 4,046 71.8 6.6 30%79

85%

Table 108 shows the storage options that were identified that are given in the matrix in Annex A for the region. This table shows the full modeling assumptions for these storage options, i.e. the cost, the capacity and the earliest year that each option is available to the system Table 109 shows the CO2 transport options and Costs that were used in the model.

79

All coal plants are assumed to air-cooled, which explains the lower efficiency.


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Table 108: CO2 Storage Options, Volumes and Costs for Southern Africa Country # in

Mat-rix

Site Name Location Capacity (Gton)

Uncertainty Risk premiu

m

Storage Cost (USD/ton)

No EOR/ECBM80

Storage Cost (USD/ton) with

EOR/ECBM81

Start Year

Modelled?

South Africa 1 Karoo Basin Inland 12 very high NA - - NA No

SAF 2 Zululand Mesozoic Basin On-Shore East Coast 0.46 high 100% 15.00 15.00 2025 Yes

3 Mezosoic Algoa and Gamtoos Basin

On-Shore South Coast 0.4 high 50% 11.25 11.25 2025 Yes

4 Onshore coal fields On-Shore inland 1.2 very high NA - - NA No

5 Mesozoic Outeniqua Basin Off-shore South coast 48 high 50% 11.25 11.25 2025 Yes

6 Mesozoic Orange Basin Off-shore West coast 56 high 50% - - 2025 No

7 Mesezoic Durban Basin Off-shore East coast 42 high 50% 11.25 11.25 2025 Yes

8 Depleted oil/gas fields Off-shore South coast 0.077 medium 25% 9.38 -30.63 2020 Yes

Botswana 9 Coal fields South 3.78 high 50% 6.45 6.45 2020 Yes

BOT 10 Saline aquifers South unknown very high NA - - NA No

Mozambique 11 Coal fields Inland South 6 very high 100% 10.20 10.20 2025 Yes

MOZ 12 Depleted gas fields Off-shore South 0.1 very high 50% 11.25 -28.75 2029 Yes

13 Saline aquifer (Ibo) Off-shore North unknown very high NA - - NA No

Namibia 14 Saline aquifer Inland East unknown very high NA - - NA No

NAM 15 Depleted oil/gas fields Off-shore South 0.129 high 75% 13.13 -26.88 202982

Yes

80

Assuming a base cost of $7.5/ton CO2 then multiplied by the 1+ Risk Premium. 81

Assuming $40/ton benefit for EOR and $4.8/ton benefit for ECBM. 82

This option is meant to only be available after 2030. However, the start year was reduced to 2029 to be within the study horizon to see if it would potentially be cost effective for Namibia.


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Table 109: CO2 transport options for the Southern African region Country Transport source Transport sink Approx.

Distance Unit transport cost Transport

cost

km USD/tonCO2/100km

USD/tonCO2

South Africa Coal plant in coal fields

East coast 800 1.00 8.00

Coal plant in coal fields

South coast 1400 1.00 14.00


Botswana coal fields

100 1.00 1.00

East coast East coast 100 1.00 1.00

South coast South coast 100 1.00 1.00

Botswana Coal plant in coal fields

Coal fields 100 1.00 1.00

Mozambique


Coal fields 100 1.00 1.00


Gas fields 400 1.00 4.00

Gas plant in gas fields Gas fields 100 1.00 1.00

Namibia Coal plant in coal fields

Gas fields 600 1.00 6.00

5.14 POWER GENERATION OPTIONS FOR THE SOUTHERN AFRICAN REGION

Table 110 shows the detailed assumptions for the generic expansion options for the region. The cost boundary includes the all major parts of the unit, such as the boiler and turbine generator, and all support facilities needed to operate the plant. These support facilities include fuel receiving/handling and storage equipment; emissions control equipment when included in the plant design; wastewater-treatment facilities; and shops, offices, and cafeterias. The cost boundary also includes the interconnection substation, but not the switchyard and associated transmission lines. The switchyard and transmission lines are generally influenced by transmission system-specific conditions and therefore are not included in the cost estimate. The estimates do not include a railroad spur or cooling water intake structures as these are assumed to not be required since these plants are envisaged to be at the mine mouth and to utilize dry-cooling technologies. The capital costs do not include government tariffs that may be charged for imported labor, equipment, or materials from outside of South Africa. The costs do include shipping charges for this equipment. Contingencies have been included for all technologies evaluated, but no currency hedging costs. The amount of contingency varies among the technologies and systems based on assessment of cost risk of the various technologies. Figure 130 shows the technology learning assumptions that were applied to some of the Renewable Energy technologies that are still maturing. These are based on the progression used by the South African DOE IRP 2011 process. Note that the learning rates are driven by projections of global installed capacity rather than domestic capacity. The cost reduction is thus an exogenous input and is fixed for all the scenarios run in the model.


190

Table 110: Generic options available in the region and associated model input parameters

Plant description Fuel type Capital cost

83

USD/kW Fixed O&M

USD/kW

Variable O&M

USD/MWh

Efficiency

Available/

capacity factor

Capacity

credit84

OCGT liquid fuels Diesel 547 9.5 0.0 30% 89% 1

Combined cycle gas Gas/LNG 842 20.0 0.0 48% 90% 1

Supercritical coal Coal 2,746 61.5 6.0 37%85

85% 1

PWR nuclear86

Nuclear

fuel 6,412 0 12.9 33% 85% 1

Biomass87

Renewab

le 4,496 131.4 4.2 25% 85% 1

Bulk Wind88

Renewab

le 2,000 35.9 0.0 NA 29% 0.23

Solar thermal central receiver

Renewable

5,207 81.5 0.0 NA 41% 1

Solar PV (bulk) Renewab

le 3,896 67.8 0.0 NA 20% 0

Figure 130: Investment cost evolution due to technology learning

5.15 SCREENING CURVE ANALYSIS

Screening curves for the main power generation options for expansion are shown in Figures 131 to 134. Electricity generation costs are expressed as levelized generation cost as a function of capacity factor. Costs are estimated for different levels of carbon price (0, 25, 50 and 100 USD/ton CO2). For CCS options, costs for transport and storage were taken into account, as well as the CO2 price payment for the non-captured portion of emissions (the CO2 capture rate is 85%). Screening curve

83

PV costs are based on DOE 2011, Integrated Resource Plan for Electricity 2010-2030, costs expressed in 2010 USD using 7.4 rands to the USD and include Interest During Construction (IDC) at 8%.

84 Used in the Reserve margin constraint.

85 All coal plants are assumed to air-cooled, which explains the lower efficiency.

86 Option only available in South Africa. The costs have incorporated the 40% increase that was implemented

at the late stage of the 2011 IRP process. 87

Option only available in South Africa and Mozambique. 88

Option only available in South Africa and Namibia.

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191

analysis shows that in the case with no CO2 penalty, the most competitive option for base load (i.e. Capacity factor > 60%) is conventional coal generation, followed by natural gas and then nuclear power. At 25USD/ton, nuclear and coal are in a similar range. At 50 USD/ton, coal with CCS becomes competitive with conventional Coal without CCS, with Nuclear is the most cost effective option. At 100 USD/ton, Gas with CCS becomes competitive with Gas without CCS, with Nuclear is still being the most cost effective option.

Figure 131: Screening curves for the Southern African region - no CO2 Price


192

Figure 132: Screening curves for the Southern African region - CO2 Price of 25 USD/ton

Figure 133: Screening curves for the Southern African region - CO2 Price of 50 USD/ton

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/MW

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Supercritical Coal Supercritical Coal w CCS

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Solar Photovoltaic 2030 Solar Thermal 2030

Biomass Imported Hydro

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Figure 134: Screening curves for Southern African region - CO2 Price of 100 USD/ton

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5.16 SIMULATION RESULTS – SOUTHERN AFRICAN REGION

In this section the modeling results for the Southern African region are presented. Tables with the following outputs are shown for each scenario for the region as a whole:

- Volumes of electricity generation by technology/fuel group. - Share of electricity generation by technology/fuel group. - Installed power generation capacity by technology/fuel group. - Annual investment in new generation capacity. - The evolution of total installed capacity by technology/fuel group. - CO2 emissions from power generation by country. - Average generation costs with and without CO2 costs included.

5.16.1 REFERENCE SCENARIO

The Reference scenario shows the evolution of the system purely on a least cost basis, i.e. free construction of the most economic electricity generation technologies with only the committed build imposed as a constraint and no other policies applied.

Figure 135: Electricity generation for Southern African region – Reference Scenario

Figure 135 shows the evolution of electricity generation by technology/fuel group and Table 111 shows the share of generation by technology/fuel group. Coal dominates with the share of generation staying well above 80% of total generation over the study horizon.

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Coal Existing Coal New CCGT Nuclear

Hydro Wind Final Energy


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Table 111: Share of Electricity Generation for Southern African region – Reference scenario Coal Oil Gas Nuclear Hydro/PS Other RE Coal CCS Gas CCS Total

2010 86% 2% 0% 5% 7% 0% 0% 0% 100%

2015 87% 0% 0% 4% 7% 1% 0% 0% 100%

2020 89% 0% 0% 4% 6% 1% 0% 0% 100%

2025 87% 1% 2% 3% 6% 1% 0% 0% 100%

2030 84% 1% 3% 3% 9% 1% 0% 0% 100%

Figure 136 shows annual new investment in capacity (MW) and the total investment in billion USD. Table 112 shows the resulting evolution of installed capacity over the study horizon. Error! Reference source not found.shows the CO2 emissions by country and the average generation.

Figure 136 New Investment in Power Generation for Southern African region – Reference scenario

Table 112 Total capacity for Southern African region – Reference scenario

Total Capacity (GW) Coal Oil Gas Nuclear Hydro/ PS Other RE Total

2010 38.7 3.0 0.3 1.8 4.7 - 48.5

2015 43.1 4.1 0.4 1.8 6.1 1.1 56.7

2020 49.1 4.1 0.4 1.8 6.3 1.1 62.9

2025 46.8 6.8 4.4 1.8 8.6 1.2 69.6

2030 51.0 6.8 8.5 1.8 10.6 1.7 80.3

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Figure 137 CO2 emissions and average generation costs for Southern African region – Reference scenario

5.16.2 BASELINE SCENARIO

The main objective of this scenario is to show the evolution of the system and the role of CCS for according to the “Revised Balance” scenario of the DOE 2011 IRP with the same CO2 limit of 275Mton for South Africa, without EOR/ECBM benefits included. Table 113 shows the investments in new generation capacity according to the South African DOE 2011, IRP “Revised Balanced” expansion plan. Figure 138 shows the evolution of electricity generation by technology/fuel group and Table 114 the share of generation by technology/fuel group. Figure 139 shows annual new investment in capacity (MW) and the total investment cost in billion USD.

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Table 113: DOE 2011 IRP “Revised balance” expansion plan New build options

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2010 0 0 0 0 0 0 0 0

2011 0 0 0 0 0 0 0 0

2012 0 0 0 0 0 300 0 0

2013 0 0 0 0 0 300 0 0

2014 500 0 0 0 400 300 0 0

2015 500 0 0 0 400 300 0 0

2016 0 0 0 0 400 300 100 0

2017 0 0 0 0 400 300 100 0

2018 0 0 0 0 400 300 100 0

2019 250 0 0 0 400 300 100 0

2020 250 237 0 0 400 300 100 0

2021 250 237 0 0 400 300 100 0

2022 250 237 805 1 143 400 300 100 0

2023 250 0 805 1 183 400 300 100 1 600

2024 250 0 0 283 800 300 100 1 600

2025 250 0 805 0 1600 1000 100 1600

2026 1000 0 0 0 400 500 0 1600

2027 250 0 0 0 1600 500 0 0

2028 1000 474 690 0 0 500 0 1600

2029 250 237 805 0 0 1000 0 1600

2030 1000 948 0 0 0 1000 0 0


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Figure 138: Electricity generation for Southern African region – Baseline scenario

Table 114: Share of generation for Southern African region – Baseline scenario Coal Oil Gas Nuclear Hydro/PS Other RE Coal CCS Gas CCS Total

2010 86% 2% 0% 5% 7% 0% 0% 0% 100%

2015 86% 0% 0% 4% 7% 2% 0% 0% 100%

2020 85% 0% 0% 4% 6% 5% 0% 0% 100%

2025 72% 1% 0% 13% 6% 8% 0% 1% 100%

2030 61% 1% 1% 20% 5% 10% 0% 2% 100%

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Figure 139: New investment in power generation for Southern African Region – Baseline scenario

Table 115 shows the resulting evolution of installed capacity over the study horizon. Figure 140 shows the CO2 emissions by country and the average generation costs. Figure 141 shows the cumulative CO2 stored by location. The capacity overall is much higher than in the Reference Scenario due to the increased use of in renewable technologies and their lower availability, such that more capacity overall is required. There is some investment in gas with CCS due the requirement of meeting the stringent CO2 limit that South Africa has imposed.

Table 115: Total Capacity for Southern African region – Baseline scenario

Total Capacity (GW) Coal Oil Gas Nuclear Hydro/ PS Other RE Coal CCS Gas CCS Total

2010 38.3 3.0 0.3 1.8 4.7 - - - 48.1

2015 42.7 3.1 0.4 1.8 6.1 2.1 - - 56.3

2020 49.2 3.1 0.4 1.8 6.3 6.1 - 0.2 67.3

2025 44.0 5.5 0.9 6.6 7.8 12.5 - 0.7 78.0

2030 43.7 6.7 2.5 11.4 7.7 18.0 - 2.4 92.3

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Figure 140: CO2 emissions and average generation costs for Southern African region – Baseline scenario

Figure 141 Cumulative CO2 storage costs for Southern African region – Baseline scenario

5.16.3 BASELINE SCENARIO WITH EOR/ECBM BENEFITS

The main objective of this scenario is to show the role of CCS for in the power system according to the “Revised Balance” scenario of the DOE 2011 IRP with the same CO2 limit of 275Mton for South Africa, but this time with EOR/ECBM benefits included.

The only difference observed in this scenario compared to the previous one without EOR/ECBM benefits, is that there is some retrofit of installations with CCS on one of the South African coal plants and some export of CO2 (approximately 1Mton/annum) from this capture facility to the depleted oil/gas fields in Mozambique towards the end of the study horizon, as shown in Figure 142.

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Figure 142: Cumulative CO2 storage costs for Southern African region – Baseline with EOR/ECBM scenario

5.16.4 CO2 PRICE SCENARIO AT - 25 USD/TON

The main objective of this scenario is to show the impact of having a 25 USD/ton CO2 price on the system. The results shown are for the least-cost evolution without baseline (IRP) build constraints other than the committed build plans. I.e. this is the same as the Reference Scenario, except for the imposition of a carbon price.

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Figure 143: Electricity generation for Southern African region –25 USD/ton CO2 Price scenario

Figure 143 shows the evolution of electricity generation by technology/fuel group and Table 116 shows the share of generation by technology/fuel group. The coal share drops from 86% to 61% between 2010 and 2030, Nuclear rises to from 5% to 8%, Renewable Technologies (wind/solar and biomass) grow to 9% by 2030 and Coal with CCS has a share of 10% by 2030.

Table 116: Share of generation for Southern African region – 25 USD/ton CO2 scenario Coal Oil Gas Nuclear Hydro/PS Other RE Coal CCS Gas CCS Total

2010 86% 2% 0% 5% 7% 0% 0% 0% 100%

2015 87% 0% 0% 4% 7% 1% 0% 0% 100%

2020 88% 0% 0% 4% 7% 1% 0% 0% 100%

2025 71% 0% 3% 9% 9% 6% 1% 0% 100%

2030 61% 0% 3% 8% 9% 9% 10% 0% 100%

Figure 144 shows annual new investment in capacity (MW) and the total investment cost in billion USD. Table 117 shows the resulting evolution of installed capacity over the study horizon.

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Figure 144: New investment in power generation for Southern African region – 25 USD/ton CO2 Price scenario

Table 117: Total capacity for Southern African region – 25 USD/ton CO2 scenario

Total capacity (GW) Coal Oil Gas Nuclear Hydro/ PS Other RE Coal CCS Gas CCS Total

2010 38.3 3.0 0.3 1.8 4.7 - - - 48.1

2015 41.6 4.1 0.4 1.8 6.1 1.1 - - 55.2

2020 47.6 4.1 0.4 1.8 7.2 1.2 - - 62.3

2025 41.3 4.5 5.4 4.9 10.5 8.2 0.6 - 75.5

2030 37.4 5.2 9.1 4.9 10.6 13.4 5.9 - 86.4

Figure 145 shows the CO2 emissions by country and the average generation costs with and without CO2 costs. Figure 146 shows the cumulative CO2 stored by resevoir location.

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Figure 145: CO2 emissions and average generation costs for Southern African region – 25 USD/ton CO2 scenario

Figure 146: Cumulative CO2 storage costs for Southern African region – 25 USD/ton CO2 scenario

5.16.5 CO2 PRICE SCENARIO - 50 USD/TON

The main objective of this scenario is to show the impact of having a 50 USD/ton CO2 price on the power system. The results shown are for the least-cost evolution without baseline (IRP) build constraints other than the committed build plans, as is carried out for the 25USD/ton CO2 price Scenario shown above.

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Figure 147 shows the evolution of electricity generation by technology/fuel group and Table 118 shows the share of generation by technology/fuel group. There is a similar generation mix to the previous case, with a slightly greater role for coal wtih CCS, with 12% portfolio share by 2030.

Figure 147: Electricity Generation for Southern African region – 50 USD/ton CO2 Price scenario

Table 118: Share of generation for Southern African region –50 USD/ton CO2 scenario Coal Oil Gas Nuclear Hydro/PS Other RE Coal CCS Gas CCS Total

2010 86% 2% 0% 5% 7% 0% 0% 0% 100%

2015 87% 0% 0% 4% 7% 1% 0% 0% 100%

2020 83% 0% 0% 4% 10% 2% 0% 0% 100%

2025 70% 0% 3% 10% 9% 7% 2% 0% 100%

2030 57% 0% 3% 9% 9% 10% 12% 0% 100%

Figure 148: New investment in power generation for Southern African region –50 USD/ton CO2 Price scenario

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Error! Reference source not found. shows annual new investment in capacity (MW) and the total nvestment cost in billion USD. Table 119 shows the resulting evolution of installed capacity over the study horizon. Figure 149 shows the CO2 emissions by country and the average generation costs with and without CO2 costs. Error! Reference source not found.Error! Reference source not und. shows the cumulative CO2 stored by storage location.

Table 119: Total capacity for Southern African region –50 USD/ton CO2 scenario


2010 38.3 3.0 0.3 1.8 4.7 - - - 48.1

2015 41.6 4.1 0.4 1.8 6.1 1.1 - - 55.2

2020 47.4 4.1 0.5 1.8 8.8 2.4 - - 65.0

2025 40.8 4.1 5.5 5.0 10.5 9.7 0.8 - 76.4

2030 36.8 3.8 8.3 5.2 10.6 16.2 7.3 - 88.2

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Figure 149: CO2 emissions and average generation costs for Southern African region –50 USD/ton CO2 scenario

Figure 150: Cumulative CO2 storage costs for Southern African region –50 USD/ton CO2 scenario

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5.16.6 CO2 PRICE SCENARIO - 100 USD/TON

The main objective of this scenario is to show the impact of having a very large CO2 Price on the power system. The results shown are for the least-cost evolution without baseline (IRP) build constraints other than the committed build plans, as with the other CO2 price scenarios. Figure 151 shows the evolution of electricity generation by technology/fuel group and Table 120 shows the share of generation by technology/fuel group.

Figure 151: Electricity generation for Southern African region – 100 USD/ton CO2 Price scenario

Table 120: Share of generation for Southern African region – 100 USD/ton CO2 scenario Coal Oil Gas Nuclear Hydro/PS Other RE Coal CCS Gas CCS Total

2010 86% 2% 0% 5% 7% 0% 0% 0% 100%

2015 87% 0% 0% 4% 7% 1% 0% 0% 100%

2020 82% 0% 0% 4% 10% 3% 0% 0% 100%

2025 50% 0% 2% 16% 9% 14% 6% 2% 100%

2030 29% 0% 0% 28% 8% 18% 11% 4% 100%

The coal share drops from 86% to 29% from 2010 to 2030 and Nuclear power share rises to from 5% to 28%, Renewable energy technologies (wind/solar and biomass) ahve a share of 18% by 2030, Coal with CCS has a share of 11%, and Gas with CCS with a 4% share, also by 2030. Figure 152 shows annual new investment in capacity (MW) and the total investment in billion USD. Table 121 shows the resulting evolution of installed capacity over the study horizon. Error! Reference source not found. shows the CO2 emissions by country and the average generation costs with and without CO2 costs. Figure 154 shows the cumulative CO2 stored by storage location.

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Figure 152: New investment in power generation for Southern African region – 100 USD/ton CO2 Price scenario

Table 121: Total capacity for Southern African region – 100 USD/ton CO2 scenario


2010 37.9 3.0 0.3 1.8 4.7 - - - 47.7

2015 41.3 4.1 0.4 1.8 6.1 1.1 - - 54.8

2020 47.0 4.1 0.5 1.8 8.8 3.7 - - 66.0

2025 40.4 4.1 1.2 8.2 9.0 19.6 3.2 1.2 86.9

2030 36.4 3.8 1.2 16.2 9.1 29.9 6.8 2.6 106.0

Figure 153: CO2 emissions and average generation costs for Southern African region – 100 USD/ton CO2 scenario

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Bibliography

210

Figure 154: Cumulative CO2 storage costs for Southern African region – 100 USD/ton CO2 scenario

5.17 SCENARIO COMPARISON

This section summarizes and compares results across the different scenarios presented above. The following indicators are compared:

- Total system discounted costs; - Average generation costs with and without CO2 costs, ie the average generation cost

computed when CO2 payments are included in the total costs, and when they are not included in the total costs (these two costs are the same in scenarios where no CO2 tax/price is imposed);

- CO2 emissions and savings; - Cumulative CO2 stored; - Share of CCS technologies of total electricity generation.

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South Africa export to Botswana coal fields South Africa export to Mozambique Depleted Oil fields

Botswana coal fields Namibia Depleted Oil fields

Bibliography

211

Table 122: Comparison of results across scenarios for Southern African region Scenario

Indicator unit Referenc

e Baselin

e Baseline w

EOR 25 USD/ton w

EOR 50 USD/ton w

EOR 100 USD/ton w

EOR

Obj function billion USD

294 305 305 325 353 375

Difference billion USD

- 11 11 32 59 81

% Difference % - 4% 4% 11% 20% 28%

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cost USD

/MWh 49 55 55 63 74 85

Difference USD

/MWh - 6 6 14 25 36

% Difference % - 12% 12% 28% 51% 74%

Avg Gen Costs no CO2

cost USD

/MWh 49 55 55 51 52 58

Difference USD

/MWh - 6 6 2 3 9

% Difference % - 12% 12% 5% 6% 19%

Cumulative CO2 Mton 6,418 5,717 5,714 5,790 5,660 4,922

Difference Mton - -702 -705 -628 -758 -1,496

% Difference % - -11% -11% -10% -12% -23%

CO2 Stored Mton 0 19 23 162 177 283

CCS share gen % 0% 2% 2% 10% 12% 16%

Cum Retrofit capture Mton - - 4.0 15.4 - -

New Installation GW 45 57 57 51 53 70

Difference GW - 12 12 6 8 26

Total Installed GW 80 92 92 86 88 106

Difference GW - 12 12 6 8 26

Cum Gen. Investment billion USD

87 177 177 134 147 261

Difference billion USD

- 90 90 47 59 174

Table 123: Share of generation summary by fuel/technology group for Southern African region

Fuel/technology group

Scenario Coal Oil Gas Nuclear Hydro/PS Other RE Coal CCS Gas CCS

2010 86% 2% 0% 5% 7% 0% 0% 0%

2030 Reference 84% 1% 3% 3% 9% 1% 0% 0%

2030 Baseline 61% 1% 1% 20% 5% 10% 0% 2%

2030 Baseline EOR 61% 1% 1% 20% 5% 10% 0% 2%

2030 25 USD /tonEOR 61% 0% 3% 8% 9% 9% 10% 0%

2030 50 USD /tonEOR 57% 0% 3% 9% 9% 10% 12% 0%

2030 100 USD /ton EOR 29% 0% 0% 28% 8% 18% 11% 4%

Bibliography

212

Figure 155: Comparison of average generation costs excluding CO2 costs across scenarios for Southern African region

Figure 156: Comparison of average generation costs Including CO2 costs across scenarios for Southern African region

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Bibliography

213

Figure 157: Comparison of annual CO2 emissions across scenarios for Southern African region

5.18 COMPARISON OF SCENARIOS FOR SOUTHERN AFRICAN REGION

Current state of power systems in the Southern African region Here, the Southern African region refers to the Southern African area covering South Africa, Botswana, Mozambique and Namibia. The main characteristics of power systems in the region are:

More than 90% of the electricity generated in the region is generated in South Africa. Electricity generation is mainly based on local coal resources. Thermal power plants are old and operate at low efficiency levels. A number of coal units

will reach their operational life-time before 2030. Two large coal power plants are currently being built in South Africa in anticipation of

increasing demand and retirement of older plants. The transmission network in the region is sparse, with bottlenecks hampering regional

electricity trade. There are however some plans in place to expand existing infrastructure. Electricity prices for final consumers have until recently been very low and there has been

little incentive for investment in new generation facilities. There is currently a tariff adjustment being made for South Africa that should alleviate this

situation. Most investment in power generation has been made by government utilities (mainly Eskom), but the South African government has expressed a strong commitment to the penetration of IPPs into the system.

There is significant potential for thye development of coal all the countries considered in the region, including gas in Mozambique and Namibia, hydro in Mozambique, wind in South Africa and Namibia and solar in all the countries considered.

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Bibliography

214

Through IRP2010 South Africa has suggested an interest in pursuing a nuclear fleet program, with the first unit coming online around 2023.

System requirements for electricity generation are estimated to increase by 220 TWh over the next 20 years. These increased needs will require construction of new power plants.

South Africa has ratified the Kyoto Protocol, and has committed to quantified targets for CO2 emission reductions through the Copenhagen pledges. The other countries have signed and ratified the Kyoto protocol, but do not have any obligations to reduce emissions. In South Africa, plans to meet the target for power generation emissions have been published in the latest Integrated Resource Plan, published by the Department of Energy.

Summary of study Analyses were carried out to determine the potential for use of CCS technologies, and its competitiveness to alternatives. This consisted of three main aspects: an assessment of available underground storage volume in the region and associated storage costs, an assessment of transportation options and costs, and an assessment of technological options for CCS equipped coal and gas power plants including a CCS retrofit option. In order to achieve the ultimate analysis, a techno-economic model based on linear programming was developed and power systems were modeled for the period 2010-2030 as interconnected national systems. Key considerations in building the models are as follows: Firstly, underground storage potential in the Southern African region is estimated to be to the order of 170.2 Gton CO2. The most significant storage capacity by volume is in deep saline aquifers and rest is in oil/gas fields and coal fields. Secondly, transport of CO2 is technologically possible and cost estimates are avaialble since this process is already established. The main component influencing the cost is the distance from the power plant to the storage site. Distances of up to 250 km could be crossed without additional compression stations. Thirdly, at present, there is no large scale CCS power plant in commercial operation, and it is expected that CCS will be commercially available sometime beyond 2020. Fourthly, all costs were discounted to 2010 using uniform discount rate of 8%. Finally, the main impacts of carbon capture in terms of a power plant operation are increased internal consumption of a plant, decreased overall efficiency due to the parasitic load, and increased investment and operational costs. The final result is increased generation cost. CCS competitiveness In order to assess the competitiveness of CCS options, three scenarios with variations were simulated: Reference scenario – least cost scenario with free competition between technologies. Base line scenario – South Africa DOE IRP 2011, with and without EOR/ECBM benefits. CO2 price scenario – introduction of different levels of CO2 price with a CO2 limit on South

Africa, and with EOR/ECBM benefits included. A screening curve analysis shows that with no CO2 price, the most competitive option is conventional coal-fired generation, followed by natural gas and then nuclear. Compounding these findings, in the Reference scenario, it was found that CCS is not competitive as it is more expensive compared to other energy technology alternatives.

Bibliography

215

If a CO2 price of 25 USD/ton CO2 emitted is introduced, the cost of coal and nuclear options are almost equal, followed by gas. CCS is still more expensive than all other alternatives. A further increase in the carbon price to 50 USD/ton CO2 leaves nuclear as the most competitive, while coal, coal with CCS and gas options compete for the second place. Finally, an increase in the carbon price to 100 USD/ton CO2 leaves nuclear as it is, as the most cost competitive, but the coal with CCS takes the second place followed by gas with CCS and conventional gas and coal units. When considering the benefits of EOR, when a 40 USD/ton CO2 EOR benefit is included then the LCOE of CCS becomes comparable to normal coal plants without any CO2 price. At 25 USD/ton and 50 USD/ton price with revenues from EOR, depleted oil fields in South Africa and Mozambique are the preferred candidate storage sites as they are the cheapest options. EOR applications are limited to the South African oil/gas fields (77Mton) before 2025, although more EOR potential becomes available in Mozambique and Namibia beyond 2030 and 2040 respectively. When EOR benefits are included, it becomes viable to install some CCS retrofits on coal plants even with long transportation distance to Mozambique and Namibia. LCOE analysis indicates that ECBM becomes cost effective compared to normal coal at around 40 USD/ton CO2 price. ECBM potential is identified in Botswana from 2025 onwards. The MESSAGE model analysis shows that at 100 USD/ton, storing CO2 in coal fields with ECBM benefits in Botswana through CCS becomes viable option for South Africa and Botswana. Storing CO2 in the depleted oil fields of Namibia could also become an option beyond 2040 if EOR benefits are included. It is noted that even with ECBM benefits, fossil plants with CCS are not competitive with nuclear plants. In summary, it is suggested that CCS technologies could potentially have a role in helping South Africa meeting its CO2 target for power generation, especially if EOR/ECBM benefits are available. However, regional cooperation will be required to utilize the available storage sites most efficiently.

Bibliography

216

BIBLIOGRAPHY

Andricevic, R., Gotovac, H., Loncar, M., and Srzic, V., Risk Assessment from oil waste disposal in deep wells. Risk Conference, Cephalonia, Greece, 5-7 May 2008. Atlas on geological storage of carbon dioxide in South Africa, Council of Geoscience, 2010, 51p + appendix. Bachu, S. and Rothenburg, L., 2003. Carbon dioxide sequestration in salt caverns: capacity and long-term fate. In: Proceedings of the second Annual Conference on carbon dioxide sequestration (CD-ROM). Alexandria, VA, 2003, 12p. BROCK, W.R., and BRYAN, L.A., Summary Results of CO2 EOR Field Tests, 1972 – 1987; Paper SPE 18977, presented at the SPE Joint Rocky Mountain Regional/Low Permeability Reservoirs and Exhibition, Denver, CO, March 6 – 8, 1989. Clough,, L.D., 2008. Energy profile of Southern Africa. In: Encyclopedia of Earth, Cleveland, C.J. (ed.), National Council for Science and the Environment. Cokorilo, V., Lilic, N., Purga, J., Milisavljevic, V., Oil shale potential in Serbia. Oil Shale, vol. 26, No4, pp 451-462, 2009. De Koninck, H., Mikunda, T., Cuamba, B., Schultz, R. and Zhou, P., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia. ECN Report ECN-E--10-065 Dimitrovic, D., Current status of CO2 injection projects in Croatia. CO2NET EAST Regionial Workshop for CEE and EE Countries- CCS Response to Climate Changes. Zagreb Feb 2007. Dolton, G.L., 2006. Pannonian Basin Province, Central Europe (Province 4808) – Petroleum Geology, Total Petroleum Systems, and Petroleum Resource assessment. USGS Bulletin 2204-B, 47p. Dubljevic, V., Oil and gas in Montenegro. Governement of Montenegro, Ministry for economic development, 2008. http:www.minekon.gov.me/en/library/document Energy Strategy and Policy of Kosovo, white paper. EU Pillar, PISG-Energy Office: Lignite mining development strategy Engelbrecht, A., Golding, A., Hietkamp, S. and Scholes, B., 2004. The potential for sequestration of carbon dioxide in South Africa. CSIR Report 86DD/HT339, 54pp. Ercegovac, M., Zivotic, D., and Kostic, A., Genetic-industrial classification of brown coals in Serbia. Int. J. of Coal Geol., 68, 2006. Evans, R. T., 2009, “CO2 Applications” discussion and reply, Journal of Petroleum Technology, October, 2009, p. 81. FP6 report: EU GeoCapacity. Assessing European Capacity for Geological Storage of Carbon Dioxide. D16. WP2 Report Storage Capacity, 2006.

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Gale, J.J., 2004. Using coal seams for CO2 sequestration. Geologica Belgica 7, 99-103. Gatzen, 2009. Salt caverns for energy storage – who fills them and with what? Presentation from Frontier Economics, 3thd april 2009. http://www.tu-dresden.de/wwbwleeg/events/enerday/2009/Presentations/Christoph.Gatzen.pdf Hatziyannis, G., Review of CO2 storage capacity of Greece, Albania and FYROM. EU GeoCapacity final conference, Copenhagen, 2009. Hatziyannis, G., Falus, G., Georgiev, G., Sava, C., Assessing capacity for geological storage of carbon dioxide in central – east group of countries (EU GeoCapacity project). Energy Procedia, 2009. Holtz, M. H., Núñez, López, V., and Breton, C. L., 2005, Moving Permian Basin technology to the gulf coast: the geologic distribution of CO2 EOR potential in gulf coast reservoirs, unconventional reservoirs, in Lufholm, P. H., and Cox, D., eds.: West Texas Geological Society Publication 05-115, Fall Symposium, October 26–27. Jeffrey, L.S., 2005. Characterization of the coal resources of South Africa. The Journal f the South African Institute of Mining and Metallurgy, february 2005, p95-102. Komatina-Petrovic, S., Geology of Serbia and potential localities for geological storage of CO2. CO2NET EAST Regionial Workshop for CEE and EE Countries- CCS Response to Climate Changes. Zagreb Feb 2007. Kucharic, L., CO2 Storage opportunities in the selected new member states and candidate states of EU (on the basis of CASTOR, WP1.2 results). CO2NET EAST Regionial Workshop for CEE and EE Countries- CCS Response to Climate Changes. Zagreb Feb 2007. Mabote, A., 2010. Overview of the upstream petroleum sector of Mozambique, UK - Mozambique Investment Forum 2010. London, Dec 2nd 2010. Marko D., Moci A., Oil production history in Albania oild fields and their perspective, Technological institute for Oil & Gas. 6th UNITAR Conference on Heavy Crude and Tar Sands (1995). Mbede, E.I., 1991. The sedimentary basins of Tanzania – reviewed. Journal of African Earth Sciences (and the Middle East) 13, 291-297. McCoy, S. T, 2008, The economics of CO2 transport by pipeline and storage in saline aquifers and saline reservoirs: Carnegie Mellon University, Ph.D. dissertation Workshop for new energy policies in Southeast Europe- The Foundation for market reform. Coalmines in Serbia and Montenegro FRY Nkala, 2008. Energy firm probes coal-bed methane prospects in Botswana, Zimbabwe. Engineering News Magazine 24/08/2008, Exploration & Development section. http://www.engineeringnews.co.za/article/energy-firm-probes-coalbed-methane-prospects-in-botswana-zimbabwe-2008-10-24 Petroleum Agency SA, 2008: Brochure “Petroleum exploration – information and opportunities 2008”.

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RISC, 2009. CO2 Injection Well Cost Estimation, Report prepared for the Carbon Storage Taskforce, 17p. Schalwyck, H.J.-M., 2005. Assessment controls on reservoir performance and the affects of granulation seam mechanics in the Bredasdorp Basin, South Africa. Master thesis University of the Western Cape, Dept of Earth Sciences, 161pp. Swart, 2010. Geological sequestration of CO2 in Namibia. Workshop Presentation CCS-Africa, Windhoek 15/04/2010. Van der Spuy, D., 2010. Natural gas – un update on South Africa’s potential. SANEA, Cape Town 21 July 2010. Presentation with notes. Viljoen, J.H.A., Stapelberg, F.D.J. and Cloete, M., 2010. Technical report on the geological storage of carbon dioxide in South Africa. Council for Geoscience, 237pp.

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ANNEX A

The Balkan region

Table 124: Summary table storage optios in the Balkan region Storage option Total capacity

/ injectivity characteristics Uncertainty /

exploration needs bottlenecks Time of

availability Reference/Comment

1) Albania coal fields

n.d. Lignite coal

for the purpose of ECBM the lignite seams are not suited due to small reserves and future use for power generation (i)

Coal not suitable for ECBM

(i) FP6 report (2006)

2) Albania oil/gas fields

122 Mt (i)

effective storage capacity 111 Mt (iii)

can increase with recent / future finds

15 fields (according to available info: - 10 : Capa<10 Mt - 3: 10 Mt<Capa<20 Mt - 2 : 20 Mt<Capa<30 Mt

main oil/gas fields (oil reserves ~198MMBO / gas reserves ~0.03Tcf

v

/ vi) occur in

sandstones and limestones

depth of reservoirs varying between surface and 5000m

use depends on

Data private

available data at AKBN archive:

- 2D seismic acquired by National Oil Company, Albpetrol (1970-1993): total 18680 km, processed lines 7400 km - 2D seismic acquired by foreign companies (1992-2006): total offshore 11124 km, total onshore 2217 km

Some fields are now declining and EOR might be an option already, other fields have future depletion perspectives


(ii) Marko D., & Moci A., (1995)

(iii) Hatziyannis (2009)

(iv) Hydrocarbon potential, Invest inAlbanian natural resources (AKBN). www.akbn.gov.al

(v) Cleveland, C., 2007. Energy profile of the Balkans, In: The Encyclopedia of the Earth (http://www.eoearth.org/article/Energy_profile_of_the_Balkans)

(vi) EIA – World energy reserves (http://www.eia.doe.gov/iea/res.html) (http://www.eia.doe.gov/countries/)

http://www.akbn.gov.al/

http://www.eoearth.org/article/Energy_profile_of_the_Balkans



http://www.eia.doe.gov/iea/res.html


http://www.eia.doe.gov/countries/


Annex A

220

abandonment history

date of starting of production are given for several fields in (ii)

oil production is declining since 1990

(vi)

EOR applied since 1983 (ii)

Still exploration opportunities (e.g. 2008 large oil/gas find close to Kosovo)

vii

- 2D seismic acquired by foreign companies (1992-2006): total offshore 400 km² -exploration wells drilled by Albpetrol: 484 wells onshore - exploration wells drilled by foreign companies (after 1992): offshore wells 6, onshore wells 6

(vii) Lendman, 2008; http://www.globalresearch.ca/index.php?context=va&aid=8129

3) Albania saline aquifer

n.d. no data available for regional aquifers

Lack of data, intensive exploration required

FP6 report

4) Albania salt dome

~ 1Mt / cavity (single cavern radius 40 m and height 300 m)

estimated storage up to 50 Mt

20 Mt effective storage capacity

evaporite occurrence in Dumre

surface exposure 18 x 12 km²

vertical thickness 6 km

cap rock thickness 0 to 300 m

top depth 2000 m

need to create caverns by dissolution of salt

Seff=1%

CO2 density 0.7

6 wells in the region

Integrity evaluation?

FP6 report

(ii) Hatziyannis (2009)

Annex A

221

(ii) t/m³

5) Bosnia-Herzegovina coal fields

n.d. occurrence of several coal basins

seams at shallow depth

CBM industry not yet developed

Shallow depth FP6 report (2006)

6) Bosnia-Herzegovina oil/gas fields

n.d. historic findings but minor production

lack of reliable data

No suitable fields FP6 report (2006)

7) Bosnia-Herzegovina saline aquifer:

Sarajevo-Zenica basin

total capacity 197 Mt (conservative) / 296 Mt (theoretical)

deeper than 1000 m storage efficiency 3 %

porosity 15 %

thickness 250 m

area 792670321 m²

net/gross ratio 0.4

CO2 density at reservoir conditions 0.830 t/m³

only 1 exploration well

few seismic sections

effective thickness and geometry extrapolated

seals need to be proven

Exploration required in order to prove capacity

FP6 report (2006)

8) Croatia coal fields

n.d. n.d. no data available

no estimation in the GeoCapacity project

Lack of data FP6 report (2006)

9) Croatia oil/gas fields

189 Mt (i)

150.4 Mt in gas fields

38.4 Mt in oil fields

Injectivity n.d.

148.5 Mt (CO2NET

Total oil reserve ~69MMBO and gas ~1.0Tcf

(v)

undiscovered reserves between 41 and 145 MMBO and between 34 and 180 BCFG

(vii)

60 uneconomic HC fields 18

oil fields are more depleted and could be converted into storage sites in the near future whereas it is not the case for the gas fields

timing n.d.

Already declining oil fields and EOR opportunities, other fields will deplete in future


(ii) Kucharic (2007)

(iii) Dimitrovic (2007)

(iv) Andricevic,et al., (2008)

(v) Cleveland, C., 2007. Energy profile of the Balkans, In: The Encyclopedia of the Earth (http://www.eoearth.org/article/Energy_profile_of_the_Balkans)




Annex A

222

EAST estimation) (ii)

potential storage sites - 7 oil fields (size n.d.) - 11 gas fields (size n.d.)

data available for 3 fields (iii)

oil production is declining since 1994

(vi)

EOR projects (i) and (iii)

zutica field: - miocene sandstones - porosity 16-22 % - permeability 5-90 mD - T=110.7 °C, P= 211 bar -injection capacity 30 m³/day (~35 t/day) (iv)

ivanic field - miocene sandstones - porosity 21.5-23.6 % - permeability 14.6-79.6 mD - T=97.8 °C, P= 183 bar - injection rate: 88 t/day, no operation

(vi) EIA – World energy reserves (http://www.eia.doe.gov/iea/res.html) (http://www.eia.doe.gov/countries/)

(vii) USGS World energy (http://certmapper.cr.usgs.gov/rooms/we/index.jsp)





http://certmapper.cr.usgs.gov/rooms/we/index.jsp


Annex A

223

problem

benicanci field - miocene breccias (limestone/dolomite) - porosity 8 % - permeability 200 mD - T=123.3 °C, Pres (actual)= 165 bar - production since 1972 CO2 injection in the 3 fields: near-miscible WAG: Ivanic and Zutica; immiscible crestal injection: Benicanci. Maybe gas injection in Benicanci in the future.

10) Croatia saline aquifer : Pannonian basin

total capacity 2710 - 4066 Mt (Seff=3%)

injectivity n.d.

351 Mt (CO2NET EAST estimation)

5 structures were delineated

4 on shore + 1 off-shore

Lack of data

deep aquifer has not been drilled

few analyses of reservoir properties

geometry is known

extrapolation for thickness, porosity, temperature from existing HC fields in the

FP6 report (2006)

Kucharic (2007)

Annex A

224

region

theoretical capacity

11) Kosovo coal fields:

n.d. 2 major lignite basins

estimated reserves of 10 Gt

coal seams at shallow (60 – 120m) depth

presently under exploitation

Too shallow depth for ECBM

Energy Strategy and Policy of Kosovo, white paper. EU Pillar, PISG-Energy Office: Lignite mining development strategy

12) Kosovo: saline aquifer

n.d. n.d. no data available

no estimation in the GeoCapacity project

Lack of data

13) Macedonia coal fields

nn.n.d.

main lignite deposits exploited since 50s

no CBM industry

under exploitation

No ECBM perspective

FP6 report (2006)

14) Macedonia saline aquifer: East Vardar basin

theoretical storage capacity for the whole basin: 1050 Mt (Seff=4%)

effective capacity estimation: for an

basin filled with thick sedimentary rocks

at the base: thick beds of clastic sediments

porosity >=15%

cap rock of thick argilites (170 m)

salt content of reservoir 100000 ppm

data from MAGNA

6 wells (ii)

4 deep boreholes

Volume of the reservoir (thickness and area n.d.)

net/gross ratio unknown


(ii) Hatziyannis, (2009).

(iii) Hatziyannis et al., (2009)

Annex A

225

interval (1800-2500 m): 390 Mt

injectivity n.d.

3800 Mt (iii)

15) Montenegro oil/gas fields

n.d. some of the wells drilled by Chevron were dry: “reservoir was tight and lacked permeability” (ii)

exploration (1949-1966): - 16 wells (900m-4600 m) - geomagnetic and gravimetric maps - 2000 km 2D seismic surveys - UK -1 weel 5309 m

exploration offshore

- 5000 m 2D seismic - 2 deep wells (4700 and 4600 m)

Total seismic coverage 6500 km of 2D data (map available)

311 lm² of 3D seismic

No suitable fields Dubljevic 2008

(ii) http:www.offshore-mag.com

16) Montenegro coal fields

n.d. mineable reserves 200 10

6t of lignite

coal seams at depth shallower

n.d. Coal too shallow for ECBM

Workshop for new energy policies in Southeast Europe- The Foundation for market reform. Coalmines in Serbia

Annex A

226

than 800 m

no CBM industry

and Montenegro FRY

17) Montenegro saline aquifer

n.d. n.d. no data Lack of data

18) Serbia coal fields

n.d. proven reserves of lignite recoverable by opencast mining methods ~4 Gt (i)

2 main basins (i)

brown coal occurs in 33 locations (ii)

only 11 under exploitation

no CBM industry

depth of the seams shallower than 800 m

n.d. Coal too shallow for ECBM

(i) Workshop for new energy policies in Southeast Europe- The Foundation for market reform. Coalmines in Serbia and Montenegro FRY

(ii) Ercegovac M., et al. (2006).

19) Serbia oil/gas fields

n.d. Total oil reserve estimated at ~78MMBO, gas ~1.7Tcf

(ii / iv)

Oil production is declining slowly (iii)

Small-sized fields

Lack of data

oil production has been very low

no depleted fields yet

Future depletion

(i) Cokorilo, V., et al., (2009).

(ii) Cleveland, C., 2007. Energy profile of the Balkans, In: The Encyclopedia of the Earth (http://www.eoearth.org/article/Energy_profile_of_the_Balkans)

(iii) EIA – World energy reserves (http://www.eia.doe.gov/iea/res.html) (http://www.eia.doe.gov/countries/) (iv) USGS World energy (http://certmapper.cr.usgs.gov/rooms/we/index.jsp)

20) Serbia saline n.d. n.d. no data Lack of data, Komatina-Petrovic (2007)










Annex A

227

aquifer: Vardar basin

“17 potential localities for storage in Serbia. with a majority situated in the Vardar zone”

extensive exploration required

References reservoir matrix Balkan Andricevic, R., Gotovac, H., Loncar, M., and Srzic, V., Risk Assessment from oil waste disposal in deep wells. Risk Conference, Cephalonia, Greece, 5-7 May 2008. Cokorilo, V., Lilic, N., Purga, J., Milisavljevic, V., Oil shale potential in Serbia. Oil Shale, vol. 26, No4, pp 451-462, 2009. Dimitrovic, D., Current status of CO2 injection projects in Croatia. CO2NET EAST Regionial Workshop for CEE and EE Countries- CCS Response to Climate Changes. Zagreb Feb 2007. Dubljevic, V., Oil and gas in Montenegro. Governement of Montenegro, Ministry for economic development, 2008. http:www.minekon.gov.me/en/library/document Energy Strategy and Policy of Kosovo, white paper. EU Pillar, PISG-Energy Office: Lignite mining development strategy Ercegovac, M., Zivotic, D., and Kostic, A., Genetic-industrial classification of brown coals in Serbia. Int. J. of Coal Geol., 68, 2006. FP6 report: EU GeoCapacity. Assessing European Capacity for Geological Storage of Carbon Dioxide. D16. WP2 Report Storage Capacity, 2006. Hatziyannis, G., Review of CO2 storage capacity of Greece, Albania and FYROM. EU GeoCapacity final conference, Copenhagen, 2009. Hatziyannis, G., Falus, G., Georgiev, G., Sava, C., Assessing capacity for geological storage of carbon dioxide in central – east group of countries (EU GeoCapacity project). Energy Procedia, 2009. Komatina-Petrovic, S., Geology of Serbia and potential localities for geological storage of CO2. CO2NET EAST Regionial Workshop for CEE and EE Countries- CCS Response to Climate Changes. Zagreb Feb 2007. Kucharic, L., CO2 Storage opportunities in the selected new member states and candidate states of EU (on the basis of CASTOR, WP1.2 results). CO2NET EAST Regionial Workshop for CEE and EE Countries- CCS Response to Climate Changes. Zagreb Feb 2007.

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228

Marko D., Moci A., Oil production history in Albania oild fields and their perspective, Technological institute for Oil & Gas. 6th UNITAR Conference on Heavy Crude and Tar Sands (1995). Workshop for new energy policies in Southeast Europe- The Foundation for market reform. Coalmines in Serbia and Montenegro FRY

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229

The Southern African region

table 125: Summary table storage options Southern African region

Storage option Total capacity / injectivity

characteristics Uncertainty / exploration needs

Bottlenecks Time of availability

Reference/source

1) South Africa on-shore saline aquifer: Paleozoic Main Karoo Basin

Capacity is questionable - if containment works then an estimate of ~12Gton total capacity could be calculated

iii

Low injectivity

Highly compartmenta-lized

Large (~700.000km

2)

basin with reservoir and seal formations

Generally very low porosity / permeability with highest values in limited zones, especially in the northern Karoo

iii

k 0 – 1,3Diii

Compartmentalized by dyke & sill intrusions

depth of more porous zones is critical and migration risk towards shallower zones

Data density low

Heterogeneity moderate to high

Dolerite intrusions may seal, but also are associated with flow pathways (e.g. natural gas seeps and groundwater paths)

Exploration needs high, but seismic imaging is hampered by dolerite intrusions

Containment unsure

Injectivity low

i) Atlas on geological storage of carbon dioxide in South Africa

ii) Petroleum Agency SA: Petroleum exploration – information and opportunities 2008. (www.petroleumagencysa.com)

iii) Viljoen et al., 2010. Technical report on the geological storage of carbon dioxide in South Africa

2) South Africa on-shore saline

~0,46 Gtoni

Containment n.d.

Covers area of ~7.500km

2

Thick sandstones

Caprocks and lateral seals need to be proven

containment unsure

intense


ii) Viljoen et al., 2010. Technical

http://www.petroleumagencysa.com/

Annex A

230

aquifer: Mesozoic Zululand Basin

Injectivity n.d. with of 15-21% encountered

ii

No seals knownii

data density low

exploration needs high

exploration efforts required

report on the geological storage of carbon dioxide in South Africa

3) South Africa onshore saline aquifer: Mesozoic Algoa & Gamtoos Basins

~0,4 Gtoni

Containment n.d.

Injectivity n.d.

Algoa Basin covers ~3.900km

2 and

Gamtoos Basin ~650km

2 iii

structural closures might be expected based on oil production

ii from

offshore extension of basin

Caprocks and lateral seals need to be proven, as well as reservoirs

data density low

exploration needs high

size of individual structures

important exploration efforts needed


ii) NewAge: Algoa-Gamtoos Basins Flyer (http://alswebpage.netfirms.com/jaksbit/Simco/Algoa-Gamtoos%20Basin%20Flyer.pdf)

iii) Viljoen et al., 2010. Technical report on the geological storage of carbon dioxide in South Africa

4) South Africa on-shore coal fields: ECBM

~ 1,2 Gtoni

Injectivity low

Most coal occurrences are Shallow (300-500m

v), but

central and eastern part of basin contains deeper (up to 800m

v / 1000m

ii)

seams with CBM potential

CBM industry not yet developed, but exploration efforts ongoing

iii,

iv (e.g. Waterberg

project with

Critical depth for CO2 storage

Depends on CBM success and ECBM prospect

Potential may vary significantly between several areas within the same basin (heterogeneity in coal characteristics)

Only viable in function of ECBM perspectives

Mostly shallow coal (<800m)


ii) Jeffrey, 2005. Characterization of the coal resources of South Africa

iii) Van der Spuy, 2010. Natural gas – un update on South Africa’s potential

iv) Rodgers, 2010. Coal-bed methane: the alternative resource http://www.polity.org.za/article/coal-bed-methane-the-alternative-energy-source-2010-08-24

v) Viljoen et al., 2010. Technical report on the geological storage of carbon dioxide in South Africa

http://alswebpage.netfirms.com/jaksbit/Simco/Algoa-Gamtoos%20Basin%20Flyer.pdf



http://www.polity.org.za/article/coal-bed-methane-the-alternative-energy-source-2010-08-24



Annex A

231

estimated capacity of 19.3Mton

iii CBM

gas)

Future potential of deeper mining and/or UCG

5) South Africa off-shore saline aquifer: Mesozoic Outeniqua Basin

~ 48 Gtoni

Scale of structures n.d.

Injectivity n.d.

Alternation of sandstone reservoirs and seals gives good potential for traps

Non-hydrocarbon-prone structures next to producing and undeveloped fields

ii

Interference with petroleum exploration goals

Data density varying dependent on sub-basins (low to moderate thanks to oil/gas exploration seismic OK, well density in best areas < 1/160km

2)

Interference with petroleum exploration

Size of individual structures

Off-shore development costs high if infrastructure not adopted from former petroleum extraction


ii) Viljoen et al., 2010. Technical report on the geological storage of carbon dioxide in South Africa

6) South Africa off-shore saline aquifer: Mesozoic Orange Basin

~ 56 Gton

Size of individual structures n.d.(largest known gas field: Ibhubesi has capacity of several 10’s of Mton gas)

Injectivity n.d.

Largely unexplored

Good potential for storage sites: sands with > 10% porosity and shale intercalations as seal + regional seal

Note the far

Data density low: 1 well / 4000km

2

ii but seismic

coverage OK

Important exploration needs





Annex A

232

distance to present-day CO2-sources

7) South Africa off-shore saline aquifer: Mesozoic Durban/Zululand Basins

~ 42 Gtoni

Containment n.d.

Injectivity n.d.

Channel and basin floor fan systems could form reservoirs

ii

Seals not well developed, but marine shales could provide regional seal

ii

Durban Basin shows several (undrilled) exploration prospects at depth ~2000m (~200m water depth)

ii

Data density very low

Containment unsure

Important exploration needs




8) South Africa off-shore depleted oil/gas fields: Outeniqua Basin (mainly at Mossel Bay

i,

Bredasdorp subbasin

ii;

Pletmos, Algoa-Gamtoos subbasins

iii),

Orange Basinii

~0,062 Gton + ~0,015 Gton (future)

i

Injectivity is estimated at ~1Mton CO2/y

I,

vi

~15-30% v

k ~10 mD – 10Dv

Petroleum fields relatively small

Potential for EOR/EGR

Infrastructure installed

Production history relatively young

Several fields are declining

i: F-A/E-

M & satellite gas fields started in 1992

iv, Oribi oil

field (from

Data density fair, good for exploited fields: offshore a total of 223.000km 2D and 10.200km

2

of 3D seismic data and over 300 exploration wells

iv, especially

in Bredasdorp Basin

Most data held by Petroleum Agency SA


Timing of abandonment should match CO2 demand

When oil production declines EOR can become viable

From ~2020 onwards depletion of the first fields may start


ii) Clough, 2008: Energy profile of South Africa

iii) New Age (http://alswebpage.netfirms.com/jaksbit/Simco/Algoa-Gamtoos%20Basin%20Flyer.pdf)

iv) Petroleum Agency SA: Petroleum exploration – information and opportunities 2008. (www.petroleumagencysa.com)

v) Schalwyck, 2005. Assessment controls on reservoir performance and the affects of granulation seam




http://www.petroleumagencysa.com/

Annex A

233

(extent of Namibia’s Kudu prospect)

1997iv), Oryx oil

field (from 2000

iv) and Sable

oil field (from 2003

iv).

Production is expected to last for another decade

iv.

Infrastructure present

Pre-mature stage allows appropriate abandonment strategy (if time-wise match between source & sink)

mechanics in the Bredasdorp Basin, South Africa. Master thesis

vi) Engelbrecht et al., 2004. The potential for sequestration of carbon dioxide in South Africa.

9) Botswana coal fields: ECBM

At least ~ 3,78 Gton

i, iv / 3,67

Gtonii CBM for

total Kalahari-Karoo Basin, of which ~0,8 Gton

i

CH4 recoverable

Injectivity n.d.

Currently at “Morupule”: peak demand + only operating mine with 5 Gton coal reserve; < 1Mton/y coal production

Important coal industry (~212 Gton coal reserve

vii)

Future coal mining and / or UCG

viii

excellent CBM perspectives

vi

(currently in exploration and demonstration phase already > 65 reconnaissance wells

iii;

commercial

Coal data good thanks to mining exploration (partly private)

CBM capacity and potential for ECBM needs more exploration

Potential to combine CCS and UCG needs more exploration

Risk assessment, especially with respect to groundwater contamination, needs to be performed (70% of drinking water from wells)

Success of CBM business development

Low injectivity per well

May become viable after ~15 years of commercial CBM extraction (~2030?)

i) Clough, 2008: Energy profile of South Africa

ii) CCS – Africa / CCS: A capacity building effort in Africa / CCS in Southern Africa Factsheet – Botswana; related concept notes and presentations (ECN – DREN – EECG – Universidade Eduardo Mondlane)

iii) Rodgers, 2010. Coal-bed methane: the alternative resource http://www.polity.org.za/article/coal-bed-methane-the-alternative-energy-source-2010-08-24

iv) Geological Survey Department Botswana – coalbed methane study http://www.gov.bw/Global/MMWER/dgscbmstudy.pdf

vi) Nkala, 2008. Energy firm probes coal-bed methane prospects in Botswana, Zimbabwe

vii) Zulu Energy

viii) De Koninck et al., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2






Annex A

234

implementation by 2015

ii)

capture and storage in Botswana, Mozambique and Namibia

10) Botswana saline aquifer

n.d. Sedimentary basins (e.g. Nosop and Ncojane) inferred but lack of data

Very few data held by different parties

viii

Full exploration needed

Lack of data requiring full exploration

i) CCS – Africa / CCS: A capacity building effort in Africa / CCS in Southern Africa Factsheet – Botswana

ii) De Koninck et al., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia

11) Mozambique coal fields: ECBM

n.d. Known coal reserves in province of Tete (~6 Gton)

Mining has not started

Data density very low

High need of exploration


De Koninck et al., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia

12) Mozambique off-shore & onshore depleted gas fields in Rovuma Basin & Mozambique Basin

n.d. At least 0,106 Gton

i / 0,0486

Gton natural gasii

founds in Pande (67 Mton

i),

Temane (25,7 Mton

i), Buzi

(19,3 – 63,7 Mton

v) and

Inhassori (13,5Mton

i)

Fields

Future depletion (production started / in development and will last for

Data density OK (private): > 85000km

i /

114.000 kmvi 2D

seismic lines, 15.000km

2 3D

areavi, ~100

i /

126vi wells

i and

still ongoing exploration for hydrocarbons



Depleted fields expected from ~2030 onwards

i) National Petroleum Institute (www.inp.gov.mz)

ii) Clough, 2008: Energy profile of South Africa

iii) Sasol: World Economic Forum on Africa, Tanzania, 2010: case-study “Mozambique natural gas project”

iv) GEO ExPro March 2006

v) ENH Hidrocarbonetos de Moçambique (www.enh-mz.com)

vi) Mabote, 2010. Overview of the upstream petroleum sector of Mozambique

http://www.enh-mz.com/

Annex A

235

~25 yearsiii)

Exploration still ongoing

iv

Offshore water depth 550-770m

i

13) Mozambique: saline aquifer

n.d. ~50% sedimentary basins

ii

Petroleum fields demonstrate that structural closures might be expected: e.g. off-shore Ibo High Horst encompasses a surface area of ~1.200km

2 with

several reservoir intervals

i


More exploration needed to prove storage capacity

Only quality data available is private (petroleum exploration)


important exploration efforts needed


i) National Petroleum Institute

ii) De Koninck et al., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia

14) Namibia saline aquifer

n.d. no data below 800m depth

i

sedimentary basins (e.g. Owambo, Aranos, Nama-Karoo Basin) have low porosity (highly cemented) as far as known

Owambo Basin

Lack of data

Full exploration required

Full exploration needed

i) De Koninck et al., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia

ii) Swart, 2010. Geological sequestration of CO2 in Namibia. Workshop Presentation CCS-Africa, Windhoek 15/04/2010 (http://www.ccs-africa.org/fileadmin/ccs-

Annex A

236

contains several mounts at ~800m depth of which 40% might be storage reservoirs

i

africa/user/docs/Windhoek_04_15/04_Geological_sequestration_of_CO2_in_Namibia.pdf)

15) Namibia depleted oil/ gas fields

~129Mton estimated capacity in depleted Kudu field if all the reported reserves can be produced

unique proven offshore gas field (Kudu ~0.025 Gton CH4) not yet exploited (expected from 2014 onward); NB: this gas field belongs geologically to the Mesozoic Orange Basin (cfr. South Africa)

offshore at total depth of 4.5km and distance of 130-200km from coast

active petroleum exploration ongoing, but exploitation yet to be started up

undiscovered resources estimated at 23-312 MMBO for oil and 46-701

seismic surveys OK (private)

exploration still ongoing

not yet exploitation data

exploration still ongoing


timing of abandonment should match CO2 demand

depleted fields expected from ~2040 onwards

i) De Koninck et al., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia

ii) Swart, 2010. Geological sequestration of CO2 in Namibia. Workshop Presentation CCS-Africa, Windhoek 15/04/2010 (http://www.ccs-africa.org/fileadmin/ccs-africa/user/docs/Windhoek_04_15/04_Geological_sequestration_of_CO2_in_Namibia.pdf)

iii) http://www.offshore-technology.com/projects/kudugasfieldnamibia/

iv) USGS World energy (http://certmapper.cr.usgs.gov/rooms/we/index.jsp)

http://www.ccs-africa.org/fileadmin/ccs-africa/user/docs/Windhoek_04_15/04_Geological_sequestration_of_CO2_in_Namibia.pdf





http://www.offshore-technology.com/projects/kudugasfieldnamibia/





Annex A

237

BDFG for gas, located in relatively large fields

vi

EOR potential?

16) Namibia coal fields: ECBM

n.d. ~372Mton coal reserves at a depth of 200-300m in Aranos Basin

CBM development is starting up (since 2009) in Aranos Basin

Known coal reserves are too shallow for ECBM purposes

Shallow coal deposits

Only in case deeper CBM extraction would be developed ECBM could become a viable option

http://www.energy-pedia.com/article.aspx?articleid=136669

17) Zimbabwe coal fields: ECBM

5,1 Gton CO2 estimated in Zambez Basin

i

772 Mton CBM reserve in the Lupane/Lubimbi area

ii

2,8 Gton CBM reserve

vi

Karoo sequence in several basins with thick (up to 8m) seams; in west and southeast part of the country

Excellent CBM reserves inferred, but still in exploration phase

v

With a fast industrial boost ECBM could become a future option (cfr. San Juan Basin in

Further ECBM exploration needed

Seismic and drilling ongoing

Success of CBM business development

Low injectivity per well

When CBM becomes mature business (from ~2040 onwards?)

i) Gale, 2004. Using coal seams for CO2 sequestration

ii) Ministry of Energy & Power Development Zimbabwe (http://www.energy.gov.zw/index.php?option=com_content&view=article&id=95&Itemid=100)

iii) Itinerant Resources: http://itinerantresources.com/current_projects/project_karoo.html

iv) Zimbabwe Energy Resources (ZER): http://zimbabwe-energy-resources.com/

v) Nkala, 2008. Energy firm probes coal-bed methane prospects in Botswana, Zimbabwe.

vi) Zulu Energy (http://www.small-cap-

http://itinerantresources.com/current_projects/project_karoo.html

http://itinerantresources.com/current_projects/project_karoo.html

http://zimbabwe-energy-resources.com/

http://zimbabwe-energy-resources.com/

Annex A

238

USA) news.de/pdf/677_zuluenergyfactsheet2008screendata.pdf)

18) Tanzania coal fields

n.d. Karoo sequence in several basins

Never been fully developed

CBM potential?

Very limited data


i) http://www.tanzania.go.tz/mining.html#Coal:

ii) http://seabgems.com/Mining%20Opportunities%20Tanzania/Coal.html

19) Tanzania hydrocarbon fields (offshore)

n.d. (so far few capacity identified)

Licenses awarded, but still in exploration / appraisal phase for hydrocarbon exploitation (estimated gas reserves in SongoSongo field ~5Mton CH4)

Probably ~30 years production capacity in Mnazi Bay future depletion

Limited data (private) and high exploration needs

ii



Possible depletion of fields expected from ~2040 onwards

i) Clough, 2008: Energy profile of South Africa

ii) Mbede, 1991. The sedimentary basins of Tanzania – reviewed.

20) Zambia coal fields

n.d. Karoo sequence in several basins with thick (up to 10m) seams (especially in the Maamba area)

i

CBM exploration in beginning stage

i

Limited data Only viable in function of ECBM perspectives

n.d. i) Ministry of Energy and Water Development – Republic of Zambia, energy exploration (http://www.mewd.gov.zm/index.php?option=com_content&task=view&id=48&Itemid=72)

References Southern Africa matrix

http://www.tanzania.go.tz/mining.html#Coal

http://www.tanzania.go.tz/mining.html#Coal

Annex A

239

Atlas on geological storage of carbon dioxide in South Africa, Council of Geoscience, 2010, 51p + appendix. Clough,, L.D., 2008. Energy profile of Southern Africa. In: Encyclopedia of Earth, Cleveland, C.J. (ed.), National Council for Science and the Environment. De Koninck, H., Mikunda, T., Cuamba, B., Schultz, R. and Zhou, P., 2010. CCS in Southern Africa - An assessment of the rationale, possibilities and capacity needs to enable CO2 capture and storage in Botswana, Mozambique and Namibia. ECN Report ECN-E--10-065 Engelbrecht, A., Golding, A., Hietkamp, S. and Scholes, B., 2004. The potential for sequestration of carbon dioxide in South Africa. CSIR Report 86DD/HT339, 54pp. Gale, J.J., 2004. Using coal seams for CO2 sequestration. Geologica Belgica 7, 99-103. Jeffrey, L.S., 2005. Characterization of the coal resources of South Africa. The Journal f the South African Institute of Mining and Metallurgy, february 2005, p95-102. Mabote, A., 2010. Overview of the upstream petroleum sector of Mozambique, UK - Mozambique Investment Forum 2010. London, Dec 2

nd 2010.

Mbede, E.I., 1991. The sedimentary basins of Tanzania – reviewed. Journal of African Earth Sciences (and the Middle East) 13, 291-297. Nkala, 2008. Energy firm probes coal-bed methane prospects in Botswana, Zimbabwe. Engineering News Magazine 24/08/2008, Exploration & Development section. http://www.engineeringnews.co.za/article/energy-firm-probes-coalbed-methane-prospects-in-botswana-zimbabwe-2008-10-24 Petroleum Agency SA, 2008: Brochure “Petroleum exploration – information and opportunities 2008”. Schalwyck, H.J.-M., 2005. Assessment controls on reservoir performance and the affects of granulation seam mechanics in the Bredasdorp Basin, South Africa. Master thesis University of the Western Cape, Dept of Earth Sciences, 161pp. Swart, 2010. Geological sequestration of CO2 in Namibia. Workshop Presentation CCS-Africa, Windhoek 15/04/2010. Van der Spuy, D., 2010. Natural gas – un update on South Africa’s potential. SANEA, Cape Town 21 July 2010. Presentation with notes. Viljoen, J.H.A., Stapelberg, F.D.J. and Cloete, M., 2010. Technical report on the geological storage of carbon dioxide in South Africa. Council for Geoscience, 237pp.

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