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

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

Renewable Energy, 2021, vol. 173, issue C, 164-176

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%.

Keywords: Pumped storage; Convex planning; Reinforcement learning; Sensitivity analysis (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:173:y:2021:i:c:p:164-176

DOI: 10.1016/j.renene.2021.03.087

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