Optimal configuration of energy storage in a microgrid based on improved multi-objective particle swarm optimization

被引：0
|
作者：
Lu L. [1 ]
Chu G. [1 ]
Zhang T. [2 ]
Yang Z. [2 ]
机构：
[1] Changzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Changzhou
[2] Nanjing Institute of Technology, Nanjing
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2020年 / 48卷 / 15期
基金：
中国国家自然科学基金;
关键词：
Bi-level programming (BLP); Energy storage; Microgrid; Multi-objective particle swarm optimization algorithm; Multiple iteration direction;
D O I：
10.19783/j.cnki.pspc.191172
中图分类号：
学科分类号：
摘要：
The energy storage participation in the optimal operation of the microgrid can effectively solve the problem of system security and stability caused by large-scale grid connection of renewable energy. Based on bi-level programming theory, an energy storage optimization configuration model with load fluctuation, system cost and energy storage SOC deviation is established. An improved multi-objective particle swarm optimization algorithm is proposed to solve the model. According to the optimal similarity, the value of inertia weight is guided, and the cross-mutation operation is introduced in time to improve the convergence of the algorithm and improve the ability to jump out of the local optimal solution. To ensure the globality and uniformity of the Pareto solution set, a strategy for dynamically updating the set based on multiple iteration directions is proposed. Finally, the weight is established based on information entropy, and the optimal scheme is selected by the TOPSIS method. The modified IEEE-33 node system is used to analyze the effectiveness and superiority of the proposed algorithm in solving the optimal configuration of microgrid energy storage. © 2020, Power System Protection and Control Press. All right reserved.
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页码：116 / 124
页数：8
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