Multi-Objective Capacity Optimization of Grid-Connected Wind–Pumped Hydro Storage Hybrid Systems Considering Variable-Speed Operation

Yang Li (), Outing Li, Feng Wu, Shiyi Ma, Linjun Shi and Feilong Hong
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Yang Li: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Outing Li: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Feng Wu: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Shiyi Ma: China Renewable Energy Engineering Institute, Beijing 100120, China
Linjun Shi: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Feilong Hong: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China

Energies, 2023, vol. 16, issue 24, 1-17

Abstract: The coordination of pumped storage and renewable energy is regarded as a promising avenue for renewable energy accommodation. Considering wind power output uncertainties, a collaborative capacity optimization method for wind–pumped hydro storage hybrid systems is proposed in this work. Firstly, considering the fluctuation of wind power generation caused by the natural seasonal weather and inherent uncertainties of wind power outputs, a combined method based on the generative adversarial network and K-means clustering algorithm is presented to construct wind power output scenarios. Then, a multi-objective wind–pumped storage system capacity optimization model is established with three objectives consisting of minimizing the levelized cost of energy, minimizing the net load peak–valley difference of regional power grids, and minimizing the power output deviation of hybrid systems. An inner and outer nested algorithm is proposed to obtain the Pareto frontiers based on the strength of the Pareto evolutionary algorithm II. Finally, the complementarity of wind power and pumped storage is illustrated through an analysis of numerical examples, and the advantages of variable-speed pumped storage in complementary operation with wind power over fixed-speed units are verified.

Keywords: wind–pumped hydro storage hybrid systems; capacity configuration; variable-speed pumped storage; multi-objective optimization; scenario generation (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: 2023
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