Boosting Efficiency: Optimizing Pumped-Storage Power Station Operation by a Mixed Integer Linear Programming Approach

Kangkang Huang, Yanlai Zhou (), Yadong Mei, Fi-John Chang and Chong-Yu Xu
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Kangkang Huang: State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China
Yanlai Zhou: State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China
Yadong Mei: State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China
Fi-John Chang: Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan
Chong-Yu Xu: State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China

Energies, 2025, vol. 18, issue 18, 1-25

Abstract: The inherent variability and unpredictability of renewable energy output pose significant challenges to power grid stability. Pumped Storage Power Stations (PSPS) play a pivotal role in mitigating these challenges, enhancing the grid’s reliability and operational efficiency. This study proposes an advanced linear analytical method based on Mixed-Integer Linear Programming (MILP) to optimize the short-term scheduling of PSPSs. The goal is to simultaneously maximize the reduction in equivalent load fluctuations and improve power generation benefits. The model linearizes the objective functions, constraints, and decision variables, applying MILP to efficiently derive optimal dispatch solutions. Using the Heimifeng (HMF) PSPS in Hunan Province as a case study, data from four representative daily load scenarios in 2023 are employed to optimize both power output and pumping processes. The results highlight the following nonlinear, competitive relationship between load fluctuation improvements and power generation benefits: as power benefits increase the rate of improvement in load fluctuations tends to decrease. The optimal solutions demonstrate significant outcomes, with improvements exceeding 11.5% in equivalent load fluctuations across all scenarios and daily power benefits surpassing $41,100, reaching a peak of $55,700. This study introduces a robust linear analytical framework capable of simultaneously enhancing power benefits and stabilizing load fluctuations, thereby offering valuable technical support for decision-makers.

Keywords: pumped-storage power station; short-term operation; optimization algorithm; peak-shaving and valley-filling; mixed integer linear programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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