THE VALUE OF FLEXIBILITY OPTIONS FROM AN www.ee2.biz OPERATORS - PowerPoint PPT Presentation

Faculty of Business and Economics , Chair of Energy Economics, Prof. Dr. Möst THE VALUE OF FLEXIBILITY OPTIONS FROM AN www.ee2.biz OPERATOR‘S PERSPECTIVE Steffi Sch chrei eiber Co-Author: Theresa Müller 15 th IAEE European Conference 2017 Session 4 G – Flexibility & Storage II Vienna, 05.09.2017

Agenda 1 Motivation 2 Value Definition and Methodological Approach 3 Flexibility Value at the Day-Ahead-Market 4 Conclusion 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 2

More incentives for operators to activate flexibility options with rising RES-share in future years ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion • balancing of load and generation Motivation • cost-benefit optimal operation mode (portfolio optimization) • provision of ancillary services • lower need of curtailment • be prepared for growing demand for flexibility at present • low price signals at electricity market and German balancing power market Challenge • few incentives to activate or invest in flexibility options in future years • rising demand for flexible assets because of rising share of renewable energy sources (RES) and intermittent feed-in of photovoltaic and wind power plants • development of a methodology to determine the value of flexibility options (FO) from an Scope operator’s perspective • decision-making tool for activating or investing in FO drinking wind onshore photovoltaic battery storage CHP unit water pumps 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 3

Agenda 1 Motivation 2 Value Definition and Methodological Approach 3 Flexibility Value at the Day-Ahead-Market 4 Conclusion 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 4

The flexibility value mainly consists of a technical and an economic value ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion   flexibility value tech echnic ical l valu lue ec econ onomic valu lue   activation time revenues at EPEX spot and balancing power market  maximal flexibility  provision time short-term activation costs (variable)  load gradients e.g. costs of provision, call  efficiency and operation  availability consequences 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 5

The flexibility value mainly consists of a technical and an economic value ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion plannable operating to short-term responding to D + 1 D planning D - 1 D balance fluctuations in unexpected changings in horizon for activating FO demand and supply demand and supply errors errors day-ahead market intraday and balancing power market merchandising trails preventive redispatch curative redispatch balancing of balancing of balancing of power reaching high power qualities of FO recognized forecasts residual forecasts or price fluctuations and load gradients errors errors under consideration contribution flexibility = ෍ sales revenues − ෍ of technical flexibility value margin activation costs con onstraints and max max min operation reg op egime FO … Flexibility Option source: own illustration following Agricola et al. 2014 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 6

Estimation of the flexibility value of different assets at the day- ahead market in comparison to an inflexible operation mode ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion contribution margin IST / FLEX operation mode   revenues short-term activation costs  no curtailment in periods of negative EPEX spot prices IST  revenues for feed-in at positive EPEX spot price + market premium  costs for feed-in at negative EPEX spot price  curtailment of RES if EPEX spot price is negative for a period of 6 hours FLEX  market premium will lapse (six-hour-rule § 51 EEG 2017)  revenues and costs structure as above (IST)  at present not day-ahead marketed (marketed at the balancing power market as FCR) IST Scenarios  cost-benefit optimal marketed at the day-ahead market FLEX  revenues for discharging at highest price level a day  costs for charging at lowest price level a day  heat guided operation mode  revenues for electricity feed-in at positive EPEX spot prices + CHP-remuneration IST  costs for gas purchasing and electricity feed-in at negative EPEX spot prices  electricity price guided operation mode FLEX  cost-benefit optimal operation mode and intelligent use of heat storage and heating boiler  revenues and costs structure as above (IST)  water demand guided operation mode (restricted by filling level of water storage tanks) IST  revenues for pumping in periods of negative EPEX spot prices  costs of electricity purchase for pumping at positive EPEX spot prices  electricity price guided operation mode FLEX  load shifting in times of lowest electricity prices a day + optimal use of water storages 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst  revenues and costs structure as above (IST) 7

Model formulation for optimization at the day-ahead market ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion INPUT OPTIMIZATION OUTPUT  electricity price time series (day-ahead forecast) 2017, 2020, 2030, 2040 Target function  temporal resolution of 8.760 h profit maximization 𝑑𝑝𝑜𝑢𝑠𝑗𝑐𝑣𝑢𝑗𝑝𝑜 𝑛𝑏𝑠𝑕𝑗𝑜 𝑛𝑏𝑦  gas price forecast 2017, 2020, 2030, 2040  optimized sales revenues at the  CHP-remuneration = ෍ 𝑠𝑓𝑤𝑓𝑜𝑣𝑓𝑡 − day-ahead market  RES market premium of direct 𝑛𝑏𝑦 marketing model cost-minimal  quarter-hourly generation and load ෍ 𝑔𝑚𝑓𝑦𝑗𝑐𝑗𝑚𝑗𝑢𝑧 𝑏𝑑𝑢𝑗𝑤𝑏𝑢𝑗𝑝𝑜 𝑑𝑝𝑡𝑢𝑡 generation profiles (reference year 2016) 𝑛𝑗𝑜  optimized  techno-economic characteristics of electricity and fuel considered assets in €/ MW·a procurement at  operation management regime / the day-ahead market constraints  under consideration of technical constraints  heat demand (reference year 2016) 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 8

Agenda 1 Motivation 2 Value Definition and Methodological Approach 3 Flexibility Value at the Day-Ahead-Market 4 Conclusion 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 9

Flexibility value of wind onshore and photovoltaic power plant at the day-ahead market ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion  FLEX value due to 300 curtailment of RES 242 ∆ contribution margin 250 [FLEX - IST] [€/MW∙a ] under consideration 186 of six-hour-rule 200 § 51 EEG rather 150 169 minor 136 100  cost savings of 55 50 curtailment in 8 4 0 periods ≥ 6 hours of 0 negative spot prices 2017 [35%] 2020 [41%] 2030 [57%] 2040 [69%] too low year [RES-share of brutto generation]  no valuable cost- PV delta contribution margin wind onshore delta contribution margin benefit relationship six-hour-rule § 51 EEG 2017  elimination of market premium (ex post) if the spot price is negative for a period of ≥ 6 hours  opportunity costs of curtailment = 0 €  reliable price forecast necessary 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 10

Flexibility value of a battery storage (lithium-polymer) at the day-ahead market ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion  electricity price max. contribution margin [FLEX] 40.000 guided operation 34.457 mode of battery storage = increasing 30.000 [€/MW∙a] FLEX value with 23.612 higher RES-share and rising price volatility 20.000 13.911  charging at lowest electricity price a day 8.517 10.000  discharging at highest electricity prices a day 0  cost-benefit optimal 2017 [35%] 2020 [41%] 2030 [57%] 2040 [69%] operation mode at year [RES-share of brutto generation] the day-ahead market 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 11

Flexibility value of CHP unit and drinking water pumps at the day-ahead market ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion value of electricity price 25.000 22.006 ∆ contribution margin guided operation mode [FLEX - IST] [€/MW ∙ a] 20.000 [FLEX] higher than heat 15.119 guided operation mode 15.000 [IST] because of:  increasing electricity 10.000 5.214 sales revenues 4.431 5.000  lower gas costs of CHP unit 0  optimal use of heat 2017 [35%] 2020 [41%] 2030 [57%] 2040 [69%] storage and heat boiler year [RES-share of brutto generation]  ca. 30% - 35% cost 24.467 25.000 50% ∆ contribution margin [FLEX - IST] [€/MW∙a] 20.455 savings because of daily relative costs savings 45% 20.000 load shifting [FLEX] in 40% times of low electricity 15.000 35% 9.044 prices 10.000 7.644 30%  optimal use of water 5.000 25% storage 0 20% 2017 [35%] 2020 [41%] 2030 [57%] 2040 [69%] year [RES-share of brutto generation] ∆ CM = CM [FLEX - IST] relative costs savings 05.09.2017 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 12