Research on Optimal Energy Storage Scheduling Strategy Based on the Coordination of Photovoltaic Power Output and Electric Vehicles

In response to the stability challenges faced by power grids under the high - penetration of renewable energy, this paper proposes an optimal energy storage scheduling strategy that integrates the coordination of photovoltaic power output and electric vehicles (EVs). This strategy regards the charging load of electric vehicles as a virtual energy storage system (VESS). By dynamically matching the photovoltaic power output with the charging demand, it realizes the load flattening of the power grid and the efficient utilization of renewable energy. Based on the improved particle swarm optimization algorithm (IPSO), a knowledge - sharing mechanism is designed to enhance the global search ability of the algorithm and optimize the coordinated scheduling of the energy storage system and EV charging. The simulation results show that the proposed strategy can reduce the peak - valley difference of the power grid by 28.5%, relieve the peak - load pressure by 19.3%, increase the photovoltaic utilization rate to 76.8%, and optimize the operating efficiency of the energy storage system by 15.2%. The research results provide theoretical support for the source - grid - load - storage integrated system and contribute to the construction of a new power system.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1109/ceepe64987.2025.11034347
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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Research on Optimal Energy Storage Scheduling Strategy Based on the Coordination of Photovoltaic Power Output and Electric Vehicles

Zhihong Liu, Ruijun Lan, Shenghui Fu, Wen Zhang et al.
1 citations
Electric Vehicles and Infrastructure
0.73
article

Research on Optimal Energy Storage Scheduling Strategy Based on the Coordination of Photovoltaic Power Output and Electric Vehicles

Zhihong Liu, Ruijun Lan, Shenghui Fu, Wen Zhang, Shuangxi Liu, Huawei Mou
article en
1 citations

Abstract

In response to the stability challenges faced by power grids under the high - penetration of renewable energy, this paper proposes an optimal energy storage scheduling strategy that integrates the coordination of photovoltaic power output and electric vehicles (EVs). This strategy regards the charging load of electric vehicles as a virtual energy storage system (VESS). By dynamically matching the photovoltaic power output with the charging demand, it realizes the load flattening of the power grid and the efficient utilization of renewable energy. Based on the improved particle swarm optimization algorithm (IPSO), a knowledge - sharing mechanism is designed to enhance the global search ability of the algorithm and optimize the coordinated scheduling of the energy storage system and EV charging. The simulation results show that the proposed strategy can reduce the peak - valley difference of the power grid by 28.5%, relieve the peak - load pressure by 19.3%, increase the photovoltaic utilization rate to 76.8%, and optimize the operating efficiency of the energy storage system by 15.2%. The research results provide theoretical support for the source - grid - load - storage integrated system and contribute to the construction of a new power system.

China Electronic Information Industry Development (CN), Shandong Agricultural University (CN)
Affordable and clean energy
Openalex Percentile: Top 27%
Electric Vehicles and Infrastructure
0.73
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