grid-connected renewables and energy storage systems and...

Grid-Connected Renewables and Energy Storage Systems and Their CO2 Emission

Mitigation Potential in Germany: A Least Cost Analysis | Subhash Kumar, Melissa

Kley,Reinhard Madlener | UKES2016, Birmingham | 30.11.2016

Grid-Connected Renewables and Energy Storage Systems and Their

CO2 Emission Mitigation Potential in Germany: A Least Cost Analysis

Subhash Kumar, Melissa Kley & Reinhard Madlener

Institute for Future Energy Consumer and Behavior (FCN)

School of Business and Economics / E.ON Energy Research Center

RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany

UK Energy Storage Conference 2016 (UKES2016)

University of Birmingham, November 30-December 02,

2016




Contents

■ Introduction- Research Questions

■Modeling Framwork- LEAP

■Scenario Development

■Results & Discussion

■Concluding Remarks




European Directives on Renewables

Renewable Energy Directive 2009/28/EC is a European Union directive which

mandates levels of renewable energy use within the European Union.

The key objectives of the strategy are to reduce carbon dioxide emissions by

20%, to increase the share of renewable energy to 20%, and to achieve

energy savings of 20% or more




Introduction...




Modeling Framework

LEAP: Long-range Energy Alternatives Planning

≡ Energy and environmental simulation model: can reflect current situation

and develop forecasts under given assumptions

≡ Developed by Stockholm Environmental Institute (SEI) in the 1980s

≡ Consists of Modules: Demand, Transformation, Environment and

Evaluation

= In this work, the new capability of the LEAP software tool has been used to

calculate the optimal expansion and dispatch of power plants for German electric

system.

= A least cost system can optionally be calculated subject to a number of user

specified constraints including maximum annual levels of emissions for any given

pollutant (CO2, Sox, Nox, PM10, etc.) and minimum or maximum capacities for

certain plant types.

= We use LEAP’s model scenario capabilities to calculate explore different optimal

solutions under different sets of input assumptions.

= LEAP includes the capability to automatically calculate least cost capacity

expansion and dispatch of supply-side Transformation modules.




Modeling Framework

■ The objective function is to minimize the total discounted costs for each year and

for each technology

σyσtTotalDiscountedCostsy,t

■ Fuel production constraints:

Productiony,ts,f ≥ Demandy,ts,f + Consumptiony,ts,f

■ Capacity constraints:

Activityy,l,t ≤ TotalInstalledCapacityy,t ∗ CapacityFactory,t

■ Activity constraints:

σl(Activityy,l,t ∗ YearSplity,l) ≤ TotAnnCapy,t ∗ AvailFactory,t ∗ CapFactory,t

■ The calculations are based on linear programming. OSeMOSYS aims to calculate

the least-cost system




Modeling Framework




Scenario Development

Time frame: 2010 – 2050

Least-cost optimisation

Model for the electricity sector

Discount rate: 5%

BAU scenario represents high-level scenario

The other five scenarios aresub-scenarios of the BAU scenario

9

Approach and assumptions

Key assumptions

Demand

Transformation

Resources




Key Techno-Economic input parameters

Technology Start yearLifetime

[years]Efficiency [%]

Available

fraction

Nuclear 2010 40 35 0.93

Coal bituminous 2010 40 42 0.86

Gas thermal 2010 40 56 0.86

Wind offshore 2010 25 35 0.2

Wind onshore 2010 25 35 0.2

Hydro 2010 50 80 0.8

Biomass 2010 30 35 0.88

PV 2010 25 16 0.15

Geothermal 2010 20 85 0.8

Coal lignite 2010 40 38 0.92

P2Hy 2020 40 39 0.75

P2G 2020 35 41 0.74

Pumped Storage 2020 35 80 0.89

Technology Investment cost

[€/kW]

Fixed O&M cost

[€/kW]

Variable O&M

cost [€/kWh]

Nuclear 2800 70 1.9

Coal bituminous 1350 12 4

Gas thermal 619 26 3.2

Wind offshore 3500 7.7 0

Wind onshore 1180 7.7 0

Hydro 1500 13 0

Biomass 2600 37 1.8

PV 3570 10.7 0.28

Geothermal 3500 60 0

Coal lignite 1525 12 4

P2Hy1800 15 0

P2G2000 19 0

Pumped Storage1200 23 0




Results & Discussion :Reference Scenario

Installed Capacity Electricity generation

CO2 Emission




Results & Discussion: Policy Scenario




Results & Discussion: Energy Storage Scenario




Results & Discussion : DSM Scenario

Energy Demand




Results & Discussion : Smart-grid Scenario




Results & Discussion : Social costs

2025 2050




Concluding Remarks

Phase-out of nuclear power plants is feasible

DSM leads to minimised social costs

In Germany, there are already many existing Acts and Federal Governmental plan

towards heavy renewable energy implementation in the electricity mix and they are in

line with the European Union directives which is evident from the results.

The model result gives an indication towards renewable for long –term benefits.

Power-to-heat is theoretically not necessary

The results of the study suggest that implementation of renewable program at large

scale is possible technically as well as economically for Germany. The variation of

different renewable resources depends on the geographical situation.




Institute for Future Energy Consumer Needs and

Behavior (FCN)

E.ON Energy Research Center

Mathieustraße 10, 52074 Aachen

Germany

Subhash Kumar

T +49 241 80 49840

F +49 241 80 49829

[email protected]

http://www.eonerc.rwth-aachen.de

Contact

Thank you so much for your kind attention!

Any questions ?

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