Capacity optimization strategy for energy storage system to ensure power supply

Huimin Fu, Ming Shi and Miaomiao Feng

International Journal of Low-Carbon Technologies, 2023, vol. 18, 622-627

Abstract: Photovoltaic (PV) and wind power generation are very promising renewable energy sources, reasonable capacity allocation of PV–wind complementary energy storage (ES) power generation system can improve the economy and reliability of system operation. In this paper, the goal is to ensure the power supply of the system and reduce the operation cost. The PV, wind and ES system models are analyzed. The differential evolutionary (DE) algorithm is adopted to optimize the particle swarm optimization (PSO) algorithm, and the parameters of the PSO algorithm are changed through the DE algorithm to obtain better performance. We use MATLAB to verify that when the system is composed of 100 kW PV and 100 kW wind power, the battery capacity obtained by PSO algorithm is 400 kWh, while the algorithm proposed in this paper only requires 330 kWh. Although the loss of load probability of the system is improved by about 0.12%, the cost is saved by 17.5%. To improve the system operation reliability, we recommend increasing PV, wind and ES capacity at the same time rather than increasing ES capacity separately.

Keywords: capacity optimization; PSO; renewable energy; Energy storage system (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:18:y:2023:i::p:622-627.

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