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INTEGRATED ENERGY PLAN

PRESENTATION TO NCCC27 JULY 2012

Department of Energy

Contents

• High Level Approach• Objectives of the Integrated Energy Plan• Demand Modeling Approach• Optimisation Model• Key Policy Questions• High Level Work Plan

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HIGH-LEVEL APPROACH

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• Guided by National Objectives• Premised on objectives of Department• Informed by input made by various government departments• Described in the document outlining the Policy Analysis Framework

Identify key objectives for IEP

• Understand local and global challenges• Understand key drivers of future uncertainty (Plausible Futures to deal

with uncertainty)• Identify and describe implemented policies with high impact on energy

sector (Will be included as Base Case or Test Cases depending on nature)• Demand Projections• Constraints and Targets for Base Case

• Current and future technologies• Macroeconomic assumptions

Define Status Quo and implications for future trends

(Understand and define key local and global challenges)

• Problem Statement Definition• Key Policy Questions that IEP should deal with• Define key criteria and relative importance (weightings)

Define Problem Statement and Key Policy Questions

HIGH-LEVEL APPROACH

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• Alternative options• New and proposed high-impact policies• Constraints and Targets for Test Cases• Input from various studies and reports

For each Policy Question identify alternative options

• Supply optimisation based on projected future demand (for Base Case and Test Cases)

• Evaluation of output from Supply Optimisation using Multi-Criteria Decision-Making Approach

Use qualitative and quantitative approaches to

evaluate outcomes

• Will be informed by outcomes from previous stepMake recommendations

HIGH-LEVEL APPROACH

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RECO

MM

ENDA

TIO

NS

Existing High-Impact Policies and Legislation

EVAL

UATE

MO

DEL O

UTP

UT

AN

D PO

LICY

PRO

POSA

LS(M

ulti-

Crite

ria D

ecis

ion

Anal

ysis

)

Key Policy Questions

Proposed/New

High-Impact Policies and

Policy Options

Key Criteria for Evaluating Alternate Options

Demand Projections

Supply Optimisation(Least cost,

emissions and water)

MODELLINGSYSTEM

MO

DEL O

UTP

UT

(EN

ERGY

RES

OU

RCES

AN

D TE

CHN

OLO

GY O

PTIO

NS)

RES(Technologies,

Energy Carriers,Energy Services)

Test Cases

Base Case

Plausible Futures to deal with Key Uncertainties

Key Indicators

HIGH-LEVEL APPROACH

Energy planning is an iterative process which entails many feedback loops between the various stages1) A mechanism of dealing with quantitative (data-driven) as well as qualitative (expert judgement) analysis2) A parallel consideration of each of the following elements:

•Existing and future energy technologies and energy carriers•Existing and proposed policies within government which have a high-impact on the energy sector•Key Indicators outside of control which characterise current and future uncertainties•Conflicting criteria upon which different options/alternatives should be evaluated

Identifying the IEP objectives

National Objectives (MTSF)

Departmental Objectives(Strategic Plan)

IEP(National Energy Act)

These are further broken down into criteria.

The criteria are:

Organising the criteria and objectives in this way facilitates scoring the options on the criteria and examining the overall results at the level of the objectives.

Energy Security

Energy system:

Technology value chains which convert energy

commodities into useful energy services

Energy commodities and other materials

constrained by availability of local natural resources and international markets

Demand forEnergy services

driven by socio-economic needs and desires

Transport

Heat

Light

Refrigeration

Mechanical work

Environmental constraints

Coal

Crude oil

Natural gas

Wind

Solar energy

Uranium

…

Technology costs, life spans, efficiencies, discount

rate and emission factors

…

Hot water

Energy systems and their context

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IRP Energy System

IEP Electricity demand

Demand technologies

Electricity Generation

Energy Services

Refining

Resource extraction/imports

Industrial processes

Energy carriers

Modelling tools• There is more value derived from modelling processes than the

final results as the process increases our understanding of energy systems

• Energy demand models— Macro-economic drivers as input— Determine demand for energy services (heating, lighting,

transport…)• Energy supply optimisation model

— Macro-economic drivers as input— Use demand derived from demand models— Minimises the cost of the energy system for demand based

on constraints

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Energy Demand in South Africa

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Industry37%

Com-mercial

8%

Transport29%

Agricul-ture2%

Non-specified

6%

Resi-dential

18%

Percentage of Total Con-sumption

Renewables & Waste

33%

Coal37%

Electricity25%

Petroleum Products5%

Residential Usage

Cooking25%

Water Heat -ing

30%Space Heating25%

Lighting15%

Electrical Appliances5%

Residential Usage

This what we collect

This what we need

for the IEP

Hybrid Approach

Phase One: Engineering- Use existing studies on the use of energy carriers

for end use services (Institute for Energy Studies 1993, Frost & Sullivan

2012, Department of Energy 2012)

Phase Two: Econometric-Project the demand for each energy carrier using historical data (DoE-Energy Balances,

Eskom-Electricity Sales)

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Industry (8 end-use services)

MechanicalElectricity

Fans Compressor Pumps Motors

ThermalElectricity

HVAC

Water Heating

Process Heat

CoalProcess

Heat

GasProcess

Heat

LightingElectricityLighting

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Gas; 37721; 12%Coal; 182119; 60%

Electricity; 83965; 28%

HVAC; 2518.95; 1%

Fans; 5037.9

; 2%

Process Heat; 252586.35; 83%

Lighting; 3358.6; 1%Motors; 33586; 11%

Com-pres-sor;

6717.2; 2%

Process Heat39%

HVAC3%

Compressors8%

Motors40%

Lighting4%

Fans6%

Electricity End Use (83695 PJ) Total Energy

Services (303805 TJ)

Total Energy Carriers

(303805 TJ)

Gas End Use(37721 TJ)

Process Heat

100%

Coal End Use(182119 TJ)

Process Heat

100%

Overview of Demand Models (112)Sector Number of Demand Models

Residential (4 sub sectors)•Low Income Non-electrified•Low Income Electrified•Middle Income Electrified•High Income Electrified

22 demand models

Commercial 6 demand models

Industrial (9 sub sectors)•Iron and Steel•Basic Chemicals•Non-ferrous Metals•Rest of Basic Metals•Gold Mining•Coal Mining•Platinum Mining•Other Mining•Rest of Manufacturing

72 demand models

Agriculture 9 demand models

Transport 3 demand models

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Hybrid Approach

Phase Two: Econometric-Project the demand for each energy carrier using historical data (DoE-Energy Balances, Eskom-Electricity Sales)

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Bottom Up ApproachSector/Sub Sector Activity Variable

Residential Total number of households

Commercial Commercial floor space

Agriculture Tons of agricultural output

Iron and Steel Tons of iron and steel

Chemical Tons of chemical

Non-ferrous Metals Tons of non-ferrous metals

Rest of Basic Metals Tons of output for the remaining metals

Gold Mining Tons of gold

Platinum Mining Tons of platinum

Other Mining Tons of other mining output

Rest of Manufacturing Tons of production for total manufacturing

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Total Projected Energy Consumption in Residential

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1 2 3 4 5 6 7 8 9 10 11 12 13 140

100000

200000

300000

400000

500000

600000

700000

800000

Residential Sector

Cooking 40%

Lighting 5%Space Heating

12%

Water Heating 32%

Other 10%

Percentage of Total Energy

Residential Sector-Demand Energy Services

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 20250

100000

200000

300000

400000

500000

600000

700000

800000

OtherWater HeatingSpace HeatingLightingCooking

User interfaces/template

Linear program solver

(GLPK)

Results tables

Optimisation model data

and demands

Linear program(OSeMOSYS)

Model data tables

Demand models

Results analysis

Model execution

Data capture and

management

Data collection (CSIR-Promethium Carbon, Eskom, DOE)

Data tools and integration (DOE)

Third party software

OSeMOSYS enhancements (CSIR)

Components of the modelling system

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Database

Demand models(DOE, Eskom)

Demand model data

Manual processes

Automated processes

Automated spread sheets for reporting

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Typical results from modelling

April 22, 2023 23

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 20300

10

20

30

40

50

60

70

80

Total generation capacityDSMCOMAIRDSMHEATPUMDSMLTHVACDSMNEWINITDSMPROCOPTDSMSHOWHDSDSMSOLWATHEATGXRESBIOREFITGXRESESKHCOARNGXRESESKHCOCAMGXRESESKHCODUVGXRESESKHCOGROGXRESESKHCOHENGXRESESKHCOKENGXRESESKHCOKOMGXRESESKHCOKRIGXRESESKHCOKUSGXRESESKHCOLETGXRESESKHCOMAJDGXRESESKHCOMAJWGXRESESKHCOMATiGXRESESKHCOMATLGXRESESKHCOMEDGXRESESKHCOTUTGXRESESKHYDGARGXRESESKHYDVANGXRESESKKERACAGXRESESKKERANKGXRESESKKERGOUGXRESESKNUCKOEU1GXRESESKNUCKOEU2GXRESESKPSDRAGXRESESKPSINGGXRESESKPSPALGXRESESKWNDSEREGXRESHYDREFITGXRESMTPPP1GXRESNONESKHCOGXRESNONESKHYDCAHGXRESNONESKKERDOEGXRESNONESKOTHGXRESNONESKPSSTEGXRESSOLCSPREFITGXRESWND1REFITGXRESWND2REFITGXNEWGASCCGXNEWHCOFBCGXNEWHCOGENPFGXNEWHYDHCBNOR

Capa

city

(GW

)

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Typical results from modelling

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 20300

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Commodity use

GASKERBIOWNDNUCSOLHYDHCO

Cons

umpti

on (P

J)

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Typical results from modelling

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 20300

50

100

150

200

250

300

350

400

CO2 emissionsEm

issio

ns (M

t)

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Typical results from modelling

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 20300

50

100

150

200

250

300

350

400

450

Water consumptionCo

nsum

ption

(Mt)

Overall modelling process

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Modelling system

Recommendations

The test case which produces the least cost energy system while

achieving the desired outcomessuggests the most effective

policies

Optimised energy system 0

Achieves desired outcomes for base case

Optimised energy system 3

Optimised energy system 2

Optimised energy system 1

Achieves desired outcomes for test

case 1

Base case

Forecast based on

trends

Implemented policy

Reference Energy System

Test case 3

Test case 2

Test case 1Plausible

futurePolicy

options

Reference Energy System with modified

parameters

Plausible future

Plausible futures

DEFINITIONSPOLICY OPTION(S) is a feasible or reasonable line of action that government can take to steer the South African energy system in the desired direction.

BASE CASE is made up of the existing policies, legislation and regulations which are in place at the beginning of the analysis period which for the current IEP2012 process.

TEST CASE is a deviation from the base case which can come from the following changes: (a) such that either policies which are not in the base policy case, (b) macroeconomic parameters which are a deviation from the status quo e.g. high GDP growth. (c) environmental or emission limits which are different from the base case.

Main Policy QuestionGiven current policies and legislation, what is the most optimal energy mix that will ensure South Africa achieves security of energy supply at the minimum cost to the economy, while minimising emissions and accounting for water usage?

Base Case: Optimisation of supply to meet demand without policy constraints-Only the committed capacity from Policy-Adjusted IRP explicitly ‘forced’-Uncommitted capacity excluded

DEFINITION: A BASE CASE is made up of the existing policies, legislation and regulations which are in place at the beginning of the analysis period which for the current IEP2012 process.

Policy Question What is the impact of including the entire IRP as “blue print”?

Test Case : Optimisation of supply to meet demand with “Entire IRP as blueprint” constraint-Committed and uncommitted capacity from Policy-Adjusted IRP explicitly ‘forced’

DEFINITION: A TEST CASE is a deviation from the base case which can come from the following changes: (a) policies which are not in the base policy case, (b) macroeconomic parameters which are a deviation from the status quo e.g. high GDP growth. (c) environmental or emission limits which are different from the base case.

Policy Question What is the impact of excluding nuclear as recommended in the NDP

What are the possible impacts ( in terms of choice of energy carriers, technology options and costs) of the proposed Carbon Tax by National Treasury on the energy sector?

Test Case : Optimisation of supply to meet demand excluding new nuclear build-Only the committed capacity from Policy-Adjusted IRP explicitly (except nuclear) ‘forced’

Test Case : Impact of carbon taxes on the choice of energy technologies and demand sectors

Non-Quantitative Analysis of Policy Options

How can energy security and supply be achieved at community level? What are the Key elements of establishing Energy-Smart Communities?

What are the possible strategies and interventions to increase localisation and local content within energy sector?

What are the viable options for investing in foreign/regional equity oil and gas?

Energy sector policy objective: Securing supply through diversity

Energy sector policy objective: Economic growth

Energy sector policy objective: Securing supply through diversity

Policy options not necessarily informed by outputs from energy models(Specific modelling requirements may be considered for future iterations of IEP)

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HIGH-LEVEL WORKPLAN

STILL TO BE COMPLETEDTechnology data collection(Collection , review and formatting of critical technology data (More than 10% contribution towards total energy supply/consumption))Collection and formatting of demand-side dataKey Macroeconomic assumptions for future demand Demand projections for energy servicesStakeholder WorkshopsDelivery of the final dataset and data sign-offConfiguring of Test Cases in model and Model runsAnalysis and Evaluation of model outputReport WritingTable Draft in CabinetStakeholder Consultations on draft report

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HIGH-LEVEL WORKPLAN

TO BE TABLED AT STAKEHOLDER WORKSHOP*

Key Assumptions

- Assumptions on Key Driving Forces (as measured by values of Key Indicators) for Plausible Futures

-Assumptions on Key Macroeconomic Indicators (not included in Plausible Futures)

- Assumptions underpinning Demand Projections

Approach to modelling of Plausible Futures within OsemosysApproach to modelling demand for energy services within all demand sectorsKey Policy Questions and Alternative Options for each- Test Cases to be considered in the model- Other Policy Options to be consideredKey Criteria for evaluating model output (Outcome of Test Cases/Policy Options testing)

THANK YOU

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