Integrating End-User and Grid Focused Batteries and Long-Term Power-to-Gas Storage for Reaching a 100 % Renewable Energy Supply

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1 Integrating End-User and Grid Focused Batteries and Long-Term Power-to-Gas Storage for Reaching a 100 % Renewable Energy Supply M. Hlusiak, Ch. Breyer 7 th International Renewable Energy Storage Conference and Exhibition (IRES) Berlin, November 2012

2 Overview Energy Model Simulation Results Sensitivity Analysis Conclusion 2

3 Setting Model Several electricity sources and storages supply one load Region Allgäu in Southern Germany as model region inhabitants 3

4 Energy Model (grid connected part) Electricity load Hourly data from local DSO Average: 140 MW Hourly values MW 4

5 Energy Model (grid connected part) Grid One node No losses or bottlenecks considered 5

6 Energy Model (grid connected part) Renewable Resources Hydro Wind PV Hourly data from DSO 3,230 flh 50 MW limit Hourly data from local operator 1,730 flh Hourly data from global model 1,080 flh Biomass For fermentive gasification 36 MW th limit 6

7 Energy Model (grid connected part) Battery Basic model Not technology specific 7

8 Energy Model (grid connected part) Natural Gas Path NG Resource Methane Storage High pressure Gas turbine PP High efficiency closed cycle 8

9 Energy Model (grid connected part) Biomethane Path Biomass Resource Biomethane Biogas reactor CH 4 purification Methane Storage Gas turbine PP 9

10 Energy Model (grid connected part) Biogas Path Biomass Resource Biogas Reactor Biogas Storage On-site, low pressure 6 hours capacity Small IC-Generator Lower efficiency than GT Installed power: 2x biogas output 10

11 Energy Model (grid connected part) Renewable Power Methane Path Methane Generation Water electrolysis CO 2 from air CO 2 + H 2 CH 4 Methane Storage Gas turbine PP 11

12 Energy Model (consumer premises) PV-Battery-System Grid parity enabled System size optimised for maximum economic yield 12

13 Simulation Steps 1) Electricity consumer side Assumed share of participants: residential sector: 20 % agricultural sector: 70 % Determine optimum system size for self consumption Vary size of PV and battery Optimise for lowest average electricity cost Grid procured electricity: 0.28 /kwh Feedin of excess power: 0.02 /kwh 13

14 2) Cover residual load in the grid Start with single natural gas turbine (0 % RE) Size of GT: max hourly load Calculate the cheapest system with 1 % RE: Optimise sizing of: Hydro, Wind, PV, Battery, Methanation, Methane storage, Biomethane and Biogas Calculate the cheapest system with 2 % RE Simulation Steps Calculate the cheapest system with 100 % EE 14

15 Consumer Side Sim. Results: Installed Powers and Capacities Covers about 5 % RE-share with assumed participation ratio 64 MW PV and 70 MWh batteries Utility Side Technologies enter system in following order: Hydro 50 MW Wind 400 MW PV 640 MW Biomethane 18 MW th Biogas 7 MW el,avg Power-to-Methane 100 MW th Batteries 320 MWh Large methane storage 120 GWh (figures are installed capacity at 100 % RE) 15

16 Sim. Results: Cost Shares by Components Gas Turbine PP Size nearly constant Natural Gas Amount decreases linearly (=RE-share definition) 100 % RE System No single technology > 30 % of total cost PV and wind largest shares, more than half total cost 16

17 Sim. Results: Storage and Power Plant Utilisation Methanation at 2,000 to 2,400 annual full load hours Battery utilisation around 150 full cycles per year RE-share Full load hours of GT decrease continuously (1,000 hours at 100 % RE) Kink at 60 % RE is biomethane kick-in 17

18 Sensitivity Analysis: NG and Carbon Cost Natural gas price and CO 2 emission cost considered With increasung RE-share: Spread between curves decreased lower fossil fuel price risk exposure With increasing fuel cost: Minimum cost point moves to higher RE-share 18

19 Sensitivity Analysis: Storage Cost LCOE at 100 % RE for varying battery and methanation cost considered LCOE sensitivity about the same to battery and methanation price swings Baseline scenario 19

20 Sensitivity Analysis: Storage Cost Battery starts at < 400 /kwh cap Installed capacity highly price sensitive 20

21 Sensitivity Analysis: Storage Cost Methanation less price sensitive for 100 % RE system No extreme increase in power with lower prices 21

22 Sensitivity Analysis: Storage Cost Battery only Three domains for storage technologies identified Methanation and Battery Methanation only 22

23 Conclusion 100 % RE system possible for 0.15 /kwh LCOE First 50 % RE can be achieved without storage (hourly timescale) Trade-off between batteries and power-to-gas researched Model considers neither geographical nor sectorial energy exchange, all figures are valid for this model region only 23

24 Thank you for your attention. 24

25 Levelised cost of electricity 25

26 Assumptions for LCOE Invest PV (Utility) 900 /kw p Invest PV (Consumer) 1,200 /kw p Invest Wind 1,000 /kw nom Invest Hydro 2,000 /kw Invest Gas Turbine Power Plant 725 /kw el Invest Battery 220 /kwh cap Invest Methane Storage 1 /kwh cap,th Invest Methanation 1,900 /kw gas Invest Biogas (incl. storage) 3,570 /kw el,avg Biomethane price 72 /MWh th Natural gas price 50 /MWh th Interest rate (WACC) 6.4 % p.a. Lifetime battery 10 years Lifetime other power plants 25 years Efficiency Gas Turbine Power Plant 58 % Efficiency Methanation (Power to Gas) 50 % Efficiency Battery (Power to Power) 85 % 26

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