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Optimal operation value of combined wind power and energy storage in multi-stage electricity markets

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  • Díaz, Guzmán
  • Coto, José
  • Gómez-Aleixandre, Javier

Abstract

This paper provides a methodology to compute the optimal bidding by a wind power producer in a multi-stage market. The methodology is not restricted to the two-stage markets often reported in the literature—a day-ahead bid submission followed by an adjustment in the imbalance market. Instead, it allows studying any number of markets operating on the same dispatch hour. Particularly, this paper analyzes part of the Spanish market, covering the day-ahead, the six intraday, and the imbalance market. They are markets with different schedules, but this paper shows that by simply rearranging the market prices into a single equivalent market and employing the increments of power as bids, the calculations are visibly simplified; despite the different scope and gate closures. The methodology also includes a dynamic programming approach that relies on the equivalent market data to provide an optimal bidding sequence and its economic value when (i) uncertain prices and wind power production are considered, and (ii) energy storage is employed. As an application, the proposed methodology is employed to analyze the revenues derived by a wind power producer using ESS in the Spanish market.

Suggested Citation

  • Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Optimal operation value of combined wind power and energy storage in multi-stage electricity markets," Applied Energy, Elsevier, vol. 235(C), pages 1153-1168.
  • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:1153-1168
    DOI: 10.1016/j.apenergy.2018.11.035
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    1. Gomes, I.L.R. & Pousinho, H.M.I. & Melício, R. & Mendes, V.M.F., 2017. "Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market," Energy, Elsevier, vol. 124(C), pages 310-320.
    2. Khalid, Muhammad & Aguilera, Ricardo P. & Savkin, Andrey V. & Agelidis, Vassilios G., 2018. "On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting," Applied Energy, Elsevier, vol. 211(C), pages 764-773.
    3. Wang, Qi & Zhang, Chunyu & Ding, Yi & Xydis, George & Wang, Jianhui & Østergaard, Jacob, 2015. "Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response," Applied Energy, Elsevier, vol. 138(C), pages 695-706.
    4. de Bosio, Federico & Verda, Vittorio, 2015. "Thermoeconomic analysis of a Compressed Air Energy Storage (CAES) system integrated with a wind power plant in the framework of the IPEX Market," Applied Energy, Elsevier, vol. 152(C), pages 173-182.
    5. Aliasghari, Parinaz & Zamani-Gargari, Milad & Mohammadi-Ivatloo, Behnam, 2018. "Look-ahead risk-constrained scheduling of wind power integrated system with compressed air energy storage (CAES) plant," Energy, Elsevier, vol. 160(C), pages 668-677.
    6. Moradi, Jalal & Shahinzadeh, Hossein & Khandan, Amirsalar & Moazzami, Majid, 2017. "A profitability investigation into the collaborative operation of wind and underwater compressed air energy storage units in the spot market," Energy, Elsevier, vol. 141(C), pages 1779-1794.
    7. Lu, Lin & Yang, Hongxing & Burnett, John, 2002. "Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics," Renewable Energy, Elsevier, vol. 27(1), pages 1-12.
    8. Díaz, Guzmán & Gómez-Aleixandre, Javier & Coto, José & Conejero, Olga, 2018. "Maximum income resulting from energy arbitrage by battery systems subject to cycle aging and price uncertainty from a dynamic programming perspective," Energy, Elsevier, vol. 156(C), pages 647-660.
    9. Bailera, Manuel & Lisbona, Pilar, 2018. "Energy storage in Spain: Forecasting electricity excess and assessment of power-to-gas potential up to 2050," Energy, Elsevier, vol. 143(C), pages 900-910.
    10. Zárate-Miñano, Rafael & Anghel, Marian & Milano, Federico, 2013. "Continuous wind speed models based on stochastic differential equations," Applied Energy, Elsevier, vol. 104(C), pages 42-49.
    11. Berrada, Asmae & Loudiyi, Khalid & Zorkani, Izeddine, 2016. "Valuation of energy storage in energy and regulation markets," Energy, Elsevier, vol. 115(P1), pages 1109-1118.
    12. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, December.
    13. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    14. Hodge, Bri-Mathias & Brancucci Martinez-Anido, Carlo & Wang, Qin & Chartan, Erol & Florita, Anthony & Kiviluoma, Juha, 2018. "The combined value of wind and solar power forecasting improvements and electricity storage," Applied Energy, Elsevier, vol. 214(C), pages 1-15.
    15. Grothe, Oliver & Schnieders, Julius, 2011. "Spatial Dependence in Wind and Optimal Wind Power Allocation: A Copula Based Analysis," EWI Working Papers 2011-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    16. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    17. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    18. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    19. Buonomano, Annamaria & Calise, Francesco & d'Accadia, Massimo Dentice & Vicidomini, Maria, 2018. "A hybrid renewable system based on wind and solar energy coupled with an electrical storage: Dynamic simulation and economic assessment," Energy, Elsevier, vol. 155(C), pages 174-189.
    20. Grothe, Oliver & Schnieders, Julius, 2011. "Spatial dependence in wind and optimal wind power allocation: A copula-based analysis," Energy Policy, Elsevier, vol. 39(9), pages 4742-4754, September.
    21. Bayón, L. & Grau, J.M. & Ruiz, M.M. & Suárez, P.M., 2016. "A comparative economic study of two configurations of hydro-wind power plants," Energy, Elsevier, vol. 112(C), pages 8-16.
    22. Al-Swaiti, Mustafa S. & Al-Awami, Ali T. & Khalid, Mohammad Waqas, 2017. "Co-optimized trading of wind-thermal-pumped storage system in energy and regulation markets," Energy, Elsevier, vol. 138(C), pages 991-1005.
    23. Daniel R. Jiang & Warren B. Powell, 2015. "Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 525-543, August.
    24. Boomsma, Trine Krogh & Juul, Nina & Fleten, Stein-Erik, 2014. "Bidding in sequential electricity markets: The Nordic case," European Journal of Operational Research, Elsevier, vol. 238(3), pages 797-809.
    25. Bueno-Lorenzo, Miriam & Moreno, M. Ángeles & Usaola, Julio, 2013. "Analysis of the imbalance price scheme in the Spanish electricity market: A wind power test case," Energy Policy, Elsevier, vol. 62(C), pages 1010-1019.
    26. Kalavani, Farshad & Mohammadi-Ivatloo, Behnam & Zare, Kazem, 2019. "Optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a demand response program," Renewable Energy, Elsevier, vol. 130(C), pages 268-280.
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