THE VALUE OF FLEXIBILITY OPTIONS FROM AN OPERATOR S PERSPECTIVE

Transcription

1 Faculty of Business and Economics, Chair of Energy Economics, Prof. Dr. Möst THE VALUE OF FLEXIBILITY OPTIONS FROM AN OPERATOR S PERSPECTIVE Steffi Schreiber Co-Author: Theresa Müller 15 th IAEE European Conference 217 Session 4 G Flexibility & Storage II Vienna,

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

3 Scope Challenge Motivation 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 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 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 operator s perspective decision-making tool for activating or investing in FO wind onshore photovoltaic battery storage CHP unit drinking water pumps TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 3

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

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 flexibility value technical value economic value activation time maximal flexibility provision time load gradients efficiency availability revenues at EPEX spot and balancing power market short-term activation costs (variable) e.g. costs of provision, call and operation consequences TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 5

6 The flexibility value mainly consists of a technical and an economic value D - 1 ❶ Motivation ❷ Value Definition and Methodology plannable operating to balance fluctuations in demand and supply D ❸ Flexibility Value at the DA-Market short-term responding to unexpected changings in demand and supply ❹ Conclusion planning horizon for activating FO merchandising trails qualities of FO flexibility value D + 1 D - 1 D balancing - 1 of power or price fluctuations D - 1 contribution margin max = max plannable operating to balance fluctuations in plannable operating to balance reaching demand fluctuations high and power supply in demand load and gradients supply day-ahead market preventive redispatch plannable reachingoperating high power to and load gradients balance reaching fluctuations high power in load gradients demand and supply balancing of power or price fluctuations balancing of power or price fluctuations day-ahead market preventive day-ahead redispatch market preventive redispatch D short-term responding to unexpected changings in balancing of short-term balancing responding of to D demand and supply recognized forecastsunexpected residual changings forecastsin errors demand errors and supply intraday and balancing power market curative redispatch balancing of recognized D forecasts balancing of errors recognized forecasts intraday errors and balancing power market intraday and curative balancing redispatch power market curative redispatch flexibility sales revenues activation costs min short-term balancing responding of to residual forecasts balancing of unexpected errors changings in residual forecasts demand errors and supply under consideration of technical constraints and operation regime balancing of power or price fluctuations source: own illustration following Agricola et al. 214 reaching high power and load gradients balancing of recognized forecasts balancing of residual forecasts FO Flexibility Option TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 6

7 Scenarios Estimation of the flexibility value of different assets at the dayahead 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 IST FLEX IST FLEX IST FLEX IST FLEX revenues short-term activation costs no curtailment in periods of negative EPEX spot prices 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 market premium will lapse (six-hour-rule 51 EEG 217) revenues and costs structure as above (IST) at present not day-ahead marketed (marketed at the balancing power market as FCR) cost-benefit optimal marketed at the day-ahead market 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 costs for gas purchasing and electricity feed-in at negative EPEX spot prices electricity price guided operation mode 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) 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 load shifting in times of lowest electricity prices a day + optimal use of water storages TU revenues Dresden, and Chair costs of structure Energy as Economics, above (IST) Prof. Dr. Möst 7

8 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) 217, 22, 23, 24 temporal resolution of 8.76 h gas price forecast 217, 22, 23, 24 CHP-remuneration RES market premium of direct marketing model quarter-hourly generation and load profiles (reference year 216) techno-economic characteristics of considered assets operation management regime / constraints heat demand (reference year 216) Target function contribution margin max = revenues max flexibility activation costs min in /MW a under consideration of technical constraints profit maximization optimized sales revenues at the day-ahead market cost-minimal generation optimized electricity and fuel procurement at the day-ahead market TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 8

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

10 contribution margin [FLEX - IST] [ /MW a] 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 curtailment of RES under consideration of six-hour-rule 51 EEG rather minor cost savings of curtailment in periods 6 hours of negative spot prices too low no valuable costbenefit relationship [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] PV delta contribution margin wind onshore delta contribution margin six-hour-rule 51 EEG 217 elimination of market premium (ex post) if the spot price is negative for a period of 6 hours opportunity costs of curtailment = reliable price forecast necessary TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 1

11 max. contribution margin [FLEX] [ /MW a] 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 guided operation mode of battery storage = increasing FLEX value with higher RES-share and rising price volatility charging at lowest electricity price a day discharging at highest electricity prices a day cost-benefit optimal operation mode at the day-ahead market [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 11

12 contribution margin [FLEX - IST] [ /MW a] relative costs savings contribution margin [FLEX - IST] [ /MW a] 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 guided operation mode [FLEX] higher than heat guided operation mode [IST] because of: increasing electricity sales revenues lower gas costs of CHP unit optimal use of heat storage and heat boiler [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] ca. 3% - 35% cost savings because of daily load shifting [FLEX] in times of low electricity prices optimal use of water storage [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] 5% 45% 4% 35% 3% 25% 2% CM = CM [FLEX - IST] relative costs savings TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 12

13 Agenda 1 Motivation 2 Value Definition and Methodological Approach 3 Flexibility Value at the Day-Ahead-Market 4 Conclusion TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 13

14 results contribution margin [FLEX - IST] [ /MW a] Potential for electricity price guided operation mode of battery, CHP unit and pumps flexibility value of RES rather minor ❶ Motivation ❷ Value Definition and Methodology ❸ Flexibility Value at the DA-Market ❹ Conclusion battery storage pumps CHP unit wind onshore photovoltaic 217 [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] growing flexibility value at the day-ahead market with rising RES-share and growing volatility of electricity prices battery, drinking water pumps and CHP unit contribution margin of electricity price guided operation mode [FLEX] always higher than contribution margin of heat or water guided operation mode [IST] photovoltaic and wind onshore RES with limited flexibility at the day-ahead market curtailment [FLEX] not valuable under consideration of six-hour-rule 51 EEG 217 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 14

15 Faculty of Business and Economics, Chair of Energy Economics, Prof. Dr. Möst Thank you! Steffi Schreiber TU Dresden, Chair of Energy Economics Phone: Theresa Müller TU Dresden, Chair of Energy Economics Phone: Tuesday,

16 References Agricola, A.; Seidl, H.; Heuke, R.; Roon, v. S.; Hinterstocker, M. und Eberl, B. (214): dena-analyse "Entwicklung der Erlösmöglichkeiten für Flexibilität auf dem Strommarkt". Endbericht. Deutsche Energie-Agentur GmbH (dena), Berlin. Bauknecht, D.; Heinemann, C.; Koch, M.; Ritter, D.; Harthan, R.; Sachs, A.; Vogel, M.; Tröster, E. und Langanke, S. (216): Systematischer Vergleich von Flexibilitäts- und Speicheroptionen im deutschen Stromsystem zur Integration von erneuerbaren Energien und Analyse entsprechender Rahmenbedingungen. Öko-Institut e.v., Freiburg/Darmstadt. Brunner, C.; Müller, T. und Heyder, B. (215): Wettbewerb von Flexibilitätsoptionen zur besseren Integration Erneuerbarer Energien. In: bbr Leitungsbau Brunnenbau Geothermie, Spezial: Neue Leitungsnetze, S Künzel, T.; Klumpp, F. und Weidlich, A. (216): Methodische Quantifizierung der Bereitstellungskosten flexibler Systemkomponenten im deutschen Stromsystem. In: Zeitschrift für Energiewirtschaft (3/217), 41 (1), S Müller, T. und Brunner, C. (215): Flexibilitätsoptionen zur Systemintegration erneuerbarer Energien im Kostenvergleich. 9. Internationale Energiewirtschaftstagung an der TU Wien (IEWT 215), S. 1-19, Wien. Müller, T.; Michaelis, J.; Elsland, R.; Reiter, U.; Fermi, F.; Wyrwa, A.; Chen, Y.; Zöphel, C. und Kronthaler, N. (216): REflex - Analysis of the European Energy System, Overview of Techno-Economic Characteristics of Different Options for System Flexibility Provision. Schill, W. P. (213): Systemintegration erneuerbarer Energien: Die Rolle von Speichern für die Energiewende. Vierteljahreshafte zur Wirtschaftsforschung, Deutsches Institut für Wirtschaftsforschung e.v. (DIW), 82. Jg., S , Berlin. TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 16

17 Back-Up load [MW] capacity deficits capacity surpluses A downward flexibility options shifting flexibility options C time [h] B upward flexibility options positive residual load [capacity deficits] negative residual load [RES surpluses] source: own illustration following Bauknecht et al., 214 and Schill, 213 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 17

18 negative residual load [RES-surpluses] positive residual load [capacity deficits] Back-Up adaptation or flexibilisation of operation mode temporal shifting spatial shifting conventional power plants lignite hard coal gas oil nuclear electricity price guided operation mode CHP units biogas / biomass plants hydro power plants RES-curtailment wind onshore wind offshore photovoltaic downward flexibility options increase in demand Power-to-Heat (electric boiler) Power-to-Gas (water electrolysis) Power-to-X (z.b. Powerto-Mobility, Power-to- Chemicals) demand-side-management load shedding energy-intensive industry air separation electrolysis electric arc and induction furnace etc. load shifting commercial and residential sector heat pumps night storage heater air conditioning ventilators washing machines cooling machines energy-intensive industry paper industry (pulp production) cement and raw mills electric mobility batteries plug-in-hybridvehicles energy storages battery storage A-CAES, CAES heat storage pumped storage etc. electricity grid regional shifting (national) imports and exports electricity grid optimization grid expansion expansion of interconnection capacities upward flexibility options shifting flexibility options source: own illustration following Müller et al., 216 and Brunner et al., 215 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 18

19 Back-Up costs of flexibility provision FIX initial costs VARIABLE activation costs investment costs [ /kw] construction development of flexibility potential fix operating costs [ /kw a] maintenance servicing staff costs costs of provision [ /MWh el ] costs of call [ /MWh el ] costs of operation consequence [ /MWh el ] Costs which occur onetime at construction or development of the FO. Costs which occur regular and independent from actual operation of the FO. Costs which occur only if FO operates. source: own illustration following Müller and Brunner, 215 and Künzel et al., 216 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 19

20 Back-Up: Calculation of market premium for RES which are in the direct marketing model equation 1: monthly market value = σ last hour of a month first hour of a month spot price h generation h monthly spot price monthly feed in equation 2: market value = market value factor spot price equation 3: applied value = feed in remuneration + management premium equation 4: market premium = applied value market value TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 2

21 [ /MWh] market value [ /MWh] market factor Back-Up: Market value and market factor of RES , ,5 1,,95,9 217 [35%] 22 [41%] 23 [57%] 24 [69%],85 year [RES-share of brutto generation] PV market value wind onshore market value PV market factor wind onshore market factor average yearly spot price [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] applied value PV applied value wind onshore market value PV market value wind onshore market premium PV market premium wind onshore TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 21

22 absolute frequency contribution margin [ /MW a] Back-Up: Contribution margin of RES without [IST] and with curtailment [FLEX] [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] PV CM [IST] wind onshore CM [IST] PV CM [FLEX] wind onshore CM [FLEX] absolute frequency of periods ( 6 hours) with negative electricity prices [35%] [16 h] 22 [41%] [96 h] 23 [57%] [123 h] 24 [69%] [369 h] year [RES-share of brutto generation] [number of hours with negative electricity prices] TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 22

23 contribution margin [FLEX] [ /MW a] contribution margin [IST] [ /MW a] Back-Up: Revenues of electricity sales and market premium 51 EEG [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] PV electricity sales revenues [IST] wind onshore electricity sales revenues [IST] PV revenues of market premium [IST] wind onshore revenues of market premium [IST] [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] PV electricity sales revenues [FLEX] wind onshore electricity sales revenues [FLEX] PV revenues of market premium [FLEX] wind onshore revenues of market premium [FLEX] TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 23

24 :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: :: charge- and discharge power [MW] EPEX spot price [ /MWh] content of storage [MWh] EPEX spot price [ /MWh] Back-Up: Electricity price guided storage behaviour 2,5 35 2, ,5 2 1, ,5 1 5,5 1 5 charge power [MW] discharge power [MW] EPEX spot price 217 content of storage [MWh] EPEX spot price 217 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 24

25 costs and revenues [ /MW a] Back-Up: Costs and revenues of charge and discharge of a battery storage [35%] [16 h] 22 [41%] [96 h] 23 [57%] [123 h] 24 [69%] [369 h] year [RES-share of brutto generation] [number of hours with negative electricity prices] electricity procurement costs electricity sales revenues TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 25

26 electricity sales revenues [FLEX] [ /MW a] gas costs [FLEX] [ /MW a] electricity sales revenues [IST] [ /MW a] gas costs [IST] [ /MW a] Back-Up: Costs and revenues of heat and electricity price guided operation mode of a CHP unit 7. heat guided operation mode [IST] [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] electricity sales revenues CHP(el) gas costs CHP(th) gas costs heat boiler(th) electricity price guided operation mode [FLEX] [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] electricity sales revenues CHP(el) gas costs CHP(th) gas costs heat boiler(th) TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 26

27 contribution margin [ /MW a] Back-Up: Delta-contribution margin of heat [IST] and electricity price guided [FLEX] operation mode [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] contribution margin [IST] contribution margin [FLEX] TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 27

28 contribution margin [ /MW a] Back-Up: Costs of electricity procurement of drinking water pumps with [FLEX] and without [IST] load shifting 217 [35%] 22 [41%] 23 [57%] 24 [69%] year [RES-share of brutto generation] pumps contribution margin [IST] pumps contribution margin [FLEX] TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 28

29 max. balancing power revenues [operator's amount] [ /MW a] Back-Up: Flexibility value at the German balancing power market battery storage CHP unit pumps wind onshore photovoltaic - 75% - 5% - 25% 1% [217] + 25% + 5% sensitivity of balancing power prices photovoltaic SCR NEG wind SCR NEG pumps SCR POS battery storage PCR CHP unit SCR POS + NEG TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 29

30 average capacity prices of balancing power [ /MW a] Back-Up: Average capacity prices at the German balancing power market PCR SCR POS SCR NEG MCR POS MCR NEG forecast 217 source: e2m, 216 TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 3

31 max. availability [%/a] Back-Up 1% day-ahead market 9% 8% 82% 7% 6% 5% 4% 3% 47% 4% 2% 1% % 16% 15% photovoltaic wind power pumps battery storage CHP 8% generation and charge of storage load and discharge of storage TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 31

32 max. availability [%/a] Back-Up 1% 9% 8% 77% balancing power market 98% 7% 6% 5% 4% 36% 36% 3% 2% 1% % 22% 12% % % photovoltaic wind power pumps battery storage CHP negative balancing power positive balancing power TU Dresden, Chair of Energy Economics, Prof. Dr. Möst 32