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Competitive model of pumped storage power plants participating in electricity spot Market——in case of China

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  • He, YongXiu
  • Liu, PeiLiang
  • Zhou, Li
  • Zhang, Yan
  • Liu, Yang

Abstract

With the development of transmission and distribution price reform in China, pumped storage power station can not continue to be included in the effective assets of the power grid, and its cost can not be dredged through the transmission and distribution price, so it is urgent to find a way to protect its own income through the market. This paper innovatively proposes a “three-stage” competitive optimization model for pumped-storage power stations, using a quadratic programming algorithm with two consecutive iterations to convert the discrete programming problem into a linear convex programming problem, reducing the difficulty of calculation and improving the calculation accuracy. Finally, the reinforcement learning algorithm is used to obtain the real-time bidding strategy of the pumped storage power station, and continuous feedback is provided. The calculation example analysis shows that compared with the traditional model, the “three-stage” model can bring better benefits to the pumped storage power station, and when the actual value of demand fluctuates within −8%, the pumped storage power station has the ability to resist risks higher than the market average. And when the proportion of renewable energy increases from the current 8%–30%, the revenue of pumped storage power plants will drop by 20%.

Suggested Citation

  • He, YongXiu & Liu, PeiLiang & Zhou, Li & Zhang, Yan & Liu, Yang, 2021. "Competitive model of pumped storage power plants participating in electricity spot Market——in case of China," Renewable Energy, Elsevier, vol. 173(C), pages 164-176.
    • Handle: RePEc:eee:renene:v:173:y:2021:i:c:p:164-176
    DOI: 10.1016/j.renene.2021.03.087
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    References listed on IDEAS

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    1. Paine, Nathan & Homans, Frances R. & Pollak, Melisa & Bielicki, Jeffrey M. & Wilson, Elizabeth J., 2014. "Why market rules matter: Optimizing pumped hydroelectric storage when compensation rules differ," Energy Economics, Elsevier, vol. 46(C), pages 10-19.
    2. Ak, Mümtaz & Kentel, Elcin & Savasaneril, Secil, 2019. "Quantifying the revenue gain of operating a cascade hydropower plant system as a pumped-storage hydropower system," Renewable Energy, Elsevier, vol. 139(C), pages 739-752.
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    Cited by:

    1. Qikai Ma & Bo Liu & Jiang Li, 2025. "A Trading Model for the Electricity Spot Market That Takes into Account the Preference for Energy Storage Trading," Energies, MDPI, vol. 18(9), pages 1-18, May.
    2. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    3. Wang, Haifeng & Yuan, Lingling & Wang, Weijun & Song, Minghao, 2024. "Distributionally robust optimization for pumped storage power station capacity expanding based on underwater hydrogen storage introduction," Energy, Elsevier, vol. 310(C).
    4. Wang, Peng & Zhang, Yushan & Ding, Yihong & Wang, Wentao & Cui, Zhengpai & Liu, Xiaoxue, 2025. "Collaborative bidding optimization model for pumped storage plants participating in the electricity and flexible ramping markets considering multi-player game relationships: Case study of China," Energy, Elsevier, vol. 326(C).

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