Research on the optimal configuration and operation control of distributed photovoltaic energy storage systems

doi:10.19799/j.cnki.2095-4239.2025.0898

Energy Storage Science and Technology ›› 2025, Vol. 14 ›› Issue (10): 3917-3919.doi: 10.19799/j.cnki.2095-4239.2025.0898

• Energy Storage System and Engineering • Previous Articles Next Articles

Research on the optimal configuration and operation control of distributed photovoltaic energy storage systems

Yuanyi ZHANG¹(), Zhenyu LIU¹^,², Jijun MENG¹, Yuanyuan BI¹, Wenyu SUN¹

^1.State Grid Jibei Electric Co. , Ltd. Chengde Power Supply Company, Chengde 067000, Hebei, China
^2.Hebei University of Technology, Tianjin 300131, China

Received:2025-09-25 Revised:2025-10-10 Online:2025-10-28 Published:2025-10-20
Contact: Yuanyi ZHANG E-mail:rqmchwrzpgx@163.com

Abstract

Abstract:

With the increasingly serious fossil energy crisis and environmental pollution problems, building a clean, low-carbon, safe and efficient energy system has become an inevitable trend for future development. Solar energy resources, as a clean and renewable energy source, have been widely applied in distributed photovoltaic power generation systems at present. This article first elaborates on the application value of this system. Then, the constraints on the optimal configuration and operation of the system were analyzed, involving the economy of photovoltaic systems, the impact of energy storage systems on stability, and the role of power market policies and fluctuations. Finally, the optimization paths were discussed, aiming to enhance the economic efficiency, stability and environmental benefits of the system through technical means, providing a reference for the efficient application of distributed photovoltaic energy storage systems.

Key words: distributed energy storage, optimize configuration, genetic algorithm, particle swarm optimization algorithm, distributed photovoltaic

CLC Number:

TM 736

Yuanyi ZHANG, Zhenyu LIU, Jijun MENG, Yuanyuan BI, Wenyu SUN. Research on the optimal configuration and operation control of distributed photovoltaic energy storage systems[J]. Energy Storage Science and Technology, 2025, 14(10): 3917-3919.

[1]	彭伟, 郑连清, 郑天文. 分布式光伏储能系统的优化配置方法[J]. 四川电力技术, 2022(1): 45-49.
	PENG W, ZHENG L Q, ZHENG T W. Optimal configuration method of distributed photovoltaic energy storage system[J], Sichuan Electric Power Technology, 2022(1): 45-49.
[2]	吴思圆, 周富云. 直流配电网中储能容量配置原则及容量配比[J].通信电源技术, 2018, 35(9): 225-227.
	WU S Y, ZHOU F Y. The configuration principles and capacity ratios of energy storage capacity in dc distribution networks[J]. Telecom Power Technology, 2018, 35(9): 225-227.
[3]	袁见. 中国太阳能光伏产业政策效应研究[D]. 沈阳: 辽宁大学, 2013.
	YUAN J. Study on the performance of china's photovoltaic industry policy[D]. Shenyang: Liaoning University, 2013.

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Research on the optimal configuration and operation control of distributed photovoltaic energy storage systems

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