储能科学与技术 ›› 2025, Vol. 14 ›› Issue (10): 3917-3919.doi: 10.19799/j.cnki.2095-4239.2025.0898

• 储能系统与工程 • 上一篇    下一篇

分布式光伏储能系统的优化配置与运行控制研究

张媛一1(), 刘震宇1,2, 孟继军1, 毕圆圆1, 孙文宇1   

  1. 1.国网冀北电力有限公司承德供电公司,河北 承德 067000
    2.河北工业大学,天津 300131
  • 收稿日期:2025-09-25 修回日期:2025-10-10 出版日期:2025-10-28 发布日期:2025-10-20
  • 通讯作者: 张媛一 E-mail:rqmchwrzpgx@163.com
  • 作者简介:张媛一(1991—),女,硕士,高级工程师,研究方向为电气工程及其自动化、通信工程、电力监控系统网络安全,E-mail: rqmchwrzpgx@163.com.
  • 基金资助:
    国网冀北承德2024年项目(B30106240005)

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. 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

摘要:

随着化石能源危机与环境污染问题日益严重,建设清洁低碳、安全高效的能源体系已是未来发展的必然趋势,太阳能资源作为一种清洁可再生能源目前已广泛应用于分布式光伏发电系统。本文首先阐述了该系统的价值,接着分析了系统优化配置与运行的制约因素,涉及光伏系统的经济性、储能系统对稳定性的影响以及电力市场政策与波动的作用。最后探讨了优化路径,旨在通过技术手段提升系统的经济性、稳定性与环保效益,为分布式光伏储能系统的高效应用提供参考。

关键词: 分布式储能, 优化配置, 遗传算法, 粒子群算法, 分布式光伏

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

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