Berlin, June 14, nd Annual Electricity Price & Load Forecasting Forum June Tim Buber

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1 Merit Order of Energy Storages by 2030 The Impact of Storage Technologies and Market Regulation on Future Electricity Prices and the Value of Flexibility Berlin, June 14, nd Annual Electricity Price & Load Forecasting Forum June Tim Buber 1

2 Agenda Research Association for Energy Markets and Technologies Motivation and Future Challenges The Concept of the Functional Energy Storage Storage Technologies and Demand Response Limitations in Price Fluctuations 2

3 Reserach Center for Energy Economics Independent Research in Energy Economics since 60 years Cooperation with the Technische Universität München Expertise in all fields of energy economics Foundation of Research Association for Energy Markets and Technologies in 2001 Research Association for Energy Markets and Technologies Smart Energy & Smart Markets Industrial Energy Management Urban Energy Management 3

4 4 Motivation and Future Challenges

5 Sum of Lost El. Generation from RES [GWh] Total Compensatory Costs [million ] Motivation and Future Challenges Feed-In Management Deliberate RES Cut-Offs Feed-In Management Contradiction Target: High share of RES on total el. generation 5 Source: Abschätzung der Bedeutung des Einspeisemanagements nach 11 EEG und 13 Abs. 2 EnWG BWE 2012

6 Photovoltaics Predicted Capacity Leistung Wind (Onshore) Predicted Capacity Leistung Motivation and Future Challenges RES in Germany Historical Development & Political Target Annual predictions of the increase of photovoltaics and wind power capacity published by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety: 70 GW 60 GW 50 GW 40 GW 30 GW 20 GW 10 GW 0 GW FfE BMWi-0002 Flexibilisierung von DEA_ Year Jahr 45 GW 40 GW 35 GW 30 GW 25 GW 20 GW 15 GW 10 GW 5 GW 0 GW FfE BMWi-0002 Flexibilisierung von DEA_ Year Jahr Increase of capacity strongly exceeds the predictions 6

7 7 The Concept of the Functional Energy Storage

8 Functional Energy Storages Overview of Storage Technologies * ** Pumped Storage CHP + Heat Storage + Power2Heat - + Electromobility Power2Gas Further Technologies Flexibilization of Load FfE Region Model Welfare and Market-Analysis 8 Expansion Scenarios * SW Münster * * EWE

9 9 Functional Energy Storages Definition Functional Energy Storage

10 10 Storage Technologies and Demand Response

11 11 Storage Technologies and Demand Response Flexible CHP Operation - Power to Heat

12 heat Heat Storage Technologies and Demand Response Basic Scheme for a Flexible CHP System CO 2 Waste Heat CO 2 Condenser Peak Load Boiler Fuel Gas Turbine/ Steam Generator steam Steam Turbine Turbine Heat Thermal Storage Flexible CHP System electricity Electrical Heating Electricity grid / EEX Electricity District Heating Grid 12 Renewables Power Plants Renewables

13 Heating Demand Storage Technologies and Demand Response Operation Modes for Flexible CHP-Systems Electricity- Demand/ -Supply Flexible CHP- System Heating Demand Electricity- Demand/ -Supply Flexible CHP- System Heating Demand high Heating Plant CHP Storage Heating Plant CHP Storage Sink Source Not operating Electricity Heat Electr. Heating Electr. Heating Heating Plant CHP Heating Plant CHP Storage Storage low Electr. Heating Electr. Heating 13 negative Electricity Prices / EEX high

14 Storage Power in GW Power/Load in in GW GW Leistung/Last in GW Leistung/Last in GW Storage Technologies and Demand Response Functional Energy Storage exemplified by CHP Stunde im Jahr 15 Hour hour of the year Year Negative Residual-Load Residual-Load Renewable Energies CHP Flexibile CHP Renewable + CHP Hour of the Year

15 Storage Technologies and Demand Response Power2Heat - Potential e-boiler capacity max. thermal load (district heating) share SW Flensburg 30 MW 320 MW 9% Germany MW MW 9% Average secondary control reserve demand in 2012: ~2.500 MW collapse of negative control reserve market? 15

16 16 Storage Technologies and Demand Response Power-to-Gas

17 Storage Technologies and Demand Response Power-to-Gas The Concept + Large storage&transmission capacities available + Long-term storage possible Low efficiency High Investment costs [1] 17 Source: [1] Specht, Michael; Zuberbühler, Ulrich: Power-to-Gas (P2G ): Layout, operation and results of the 25 and 250 kwel research plants. Stuttgart: Zentrum für Sonnenenergie- und Wasserstoff-Forschung (ZSW), 2012

18 Storage Technologies and Demand Response Power-to-Gas Hydrogen Production Costs time of negative residual load in h/a full load hours for 1 GW electrolysis power in h/a hours of negative residual load ( +10 GW power generation for stabilization purposes) GW power generation for stabilization purposes

19 19 Storage Technologies and Demand Response Electromobility

20 Storage Technologies and Demand Response Electromobility Key Questions Key Questions: Where and when are how many vehicles charged? What is the capacity and energy for charging? What is the ratio of parking and charging duration? 20

21 Hour of Day parking probability within 15 minutes Hour Hour of of Day parking probability within 15 minutes Storage Technologies and Demand Response Electromobility Usability Factors Usability work Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su 21

22 Number of electric vehicles in million Anzahl an Elektrofahrzeugen in Mio. Storage Technologies and Demand Response Electromobility Prognosis and Impact on Residual Load Average storage capacity of traction battery in EVs: 26,5 kwh Das conenery - fast Szenario geht von 50 Mio. EV bis 2030 aus Scenario: 7 mio EVs in Jahre Year IfE DGS conenergy - fast Bundesregierung conenergy - slow RWTH Aachen Flattening of the residual load only very little benefit from V2G and DSM even for 7 Mio EVs Simplified business approach (pay for capacity not for energy)

23 23 Storage Technologies and Demand Response Flexibilization of Load

24 Storage Technologies and Demand Response Demand Side Management Average DSM-Potential for Commerce, Trade and Services MW positive MW negative (mainly night storage heating) positive = reduction of load negative = increase of load Average DSM Potential in Industry MW positive DSM Potential 410 MW negative DSM Potential Source: EWI, 2010 What about temporal availability? 24

25 25 Limitations in Price Fluctuations

26 Residual Load [GW] Limitations in Price Fluctuations Volatility of the Residual Load Scenario PV: 60 GW Wind: 60 GW Scenario PV: 30 GW Wind: 30 GW Hour of the Day FfE MOS_

27 Residual Load [GW] Limitations in Price Fluctuations Volatility of the Residual Load Scenario PV: 60 GW Wind: 60 GW Scenario PV: 30 GW Wind: 30 GW Hour of the Day FfE MOS_00064 Minimum in the morning and during noon Maximum during early noon and evening 27 Choose timeframes according to this observation in order to analyze the dynamics of the residual load

28 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load 28 Minimum of the Residual Load within Timeframe

29 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load 29 Minimum of the Residual Load within Timeframe

30 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 30 Minimum of the Residual Load within Timeframe

31 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 31 Minimum of the Residual Load within Timeframe

32 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 32 Minimum of the Residual Load within Timeframe

33 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 33 Minimum of the Residual Load within Timeframe

34 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 34 Minimum of the Residual Load within Timeframe

35 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 35 Minimum of the Residual Load within Timeframe

36 Difference between the Maximimum and Minimum of the Residual Load within used Timeframes Limitations in Price Fluctuations Volatility of the Residual Load Today 36 Minimum of the Residual Load within Timeframe

37 Limitations in Price Fluctuations Volatility of the Residual Load educated guessing on how storage technologies can influence the residual load Power 2 Heat + 2 GW Power 2 Gas GW Electromobility GW Flexibilization of Load +/- 1 2 GW Pumped Hydro Storage +/- 2-3 GW Increased Im-/Export capacities +/- 2-3 GW Today GW possible shift by storage technologies

38 Limitations in Price Fluctuations Volatility of the Residual Load Though plenty of the points lie Today within the grey shaded area we will have to expect significant price fluctuations! 38

39 Day-Ahead Price in /MWh Limitations in Price Fluctuations Day-Ahead-Analysis y = x Residual Load in GW FfE MOS-KOSI_00044 Price follows predominantly the residual load Several occurences of negative prices 39 Conclusion: No predominant influence of RES in price building mechanism visible

40 Produciton in GW Day-Ahead-Price in /MWh Limitations in Price Fluctuations Events of Negative Prices Production Tue., Solar Wind Others Coal Lignite Nuclear DA-Price 10 0 FfE MOS-KOSI_ Extrema of the day in GW Solar Wind Coal Lignite Nuclear Min Max DA-Price = Day-Ahead Price, Data-Source: transparency.eex.com

41 Limitations in Price Fluctuations Schemes of Remuneration The German Renewable Energy Act offers choice of the scheme of remuneration for feed-in. Earnings by Feed-In-Tariff [EUR] = Remuneration for Feed-In Rate [EUR/MWh] * Feed-In [MWh] Earnings by Direct Selling and Market Bonus [EUR] = Revenue at European Energy Exchange [EUR] + Market Bonus [EUR/MWh] = Remuneration for Feed-In Rate [EUR/MWh] + Feed-In * [MWh] +/- Imbalance Energy Payments [EUR] Management Bonus [EUR/MWh] - Monthly Weighted Average Price [EUR/MWh] 41

42 Limitations in Price Fluctuations Direct Selling and Negative Prices Remuneration for Feed-In Rate + Management Bonus - Monthly Weighted Average = Market Bonus + - = /MWh /MWh /MWh /MWh : Prices should not have fallen below: -81 /MWh 42

43 January 2012 Februray 2012 March 2012 April 2012 May 2012 June 2012 July 2012 August 2012 September 2012 October 2012 November 2012 December 2012 January 2013 February 2013 March 2013 April 2013 Capacity in GW Limitations in Price Fluctuations Development in the capacity of Direct-Selling PV Wind Gas Wind (Offshore) Biomass Hydro FfE MOS_ Hydro Gas Biomass Wind Offshore Solar Total in MW Jan Jun Nov Apr

44 Limitations in Price Fluctuations - Conclusion The expected increase of price fluctuations can be limited by storage technologies to a certain extend Downwards? Limited by marginal costs of emerging storage technologies Depending on available power and capacity Limited by the remuneration scheme of direct selling Upwards? Hard coal as well as gas prices Decharging capacity of storage technologies Flexibilization of Load Electromobility (depending on charging strategy) 44

45 Limitations in Price Fluctuations - Conclusion Which Markets will have to deal with increasing price fluctuations? Day-Ahead: Sufficient capacity Rare occurrences of extremely low prices chance for DSM? Control reserve: Minute Reserve: hardly any revenues possible Secondary Control Reserve: Positive: extremely low revenues, going down to zero Negative: still attractive for some applications 45 Intraday: Low online-capacity demand for high flexibility high price volatility expected. high uncertainty (grid restrictions, )

46 Thank you for your attention and the support of 46 Tim Buber: / Forschungsgesellschaft für Energiewirtschaft mbh Am Blütenanger München

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