Multi-objective Optimization of Energy Storage System with Frequency Regulation Control Under High Proportion of Renewable Energy

被引：0
|
作者：
Yang T. [1 ]
Huang Y. [1 ]
Tang J. [1 ]
Wang D. [1 ]
Zhou K. [1 ]
Zhu G. [1 ]
机构：
[1] School of Automation, Wuhan University of Technology, Wuhan
来源：
Gaodianya Jishu/High Voltage Engineering | 2023年 / 49卷 / 07期
关键词：
control strategy; energy storage system configuration; high proportion of renewable energy; multi-objective optimization; primary frequency regulation;
D O I：
10.13336/j.1003-6520.hve.20230580
中图分类号：
学科分类号：
摘要：
Energy storage plays a crucial role in high-proportion renewable energy systems, such as peak shaving, frequency regulation, and voltage regulation. However, the effectiveness of energy storage depends on its capacity and location configuration. In order to solve the problem of optimal configuration of energy storage system with frequency regulation control under high proportion of renewable energy systems, a primary frequency regulation control strategy based on nonlinear variable K coefficient is first studied, and its control parameters are optimized. On this basis, a multi-objective optimization configuration method for energy storage location and capacity is proposed for high-proportion renewable energy power systems. In the method, a multi-objective particle swarm optimization algorithm with energy storage capacity and location is used as decision variables. The system frequency fluctuation index, grid vulnerability index, and energy storage economy index are minimized as optimization objectives to obtain the Pareto solution set. After obtaining the weights of each objective through information entropy, the optimal solution is calculated using the inferior solution distance method. Finally, an actual case analysis of a regional power grid in Anyang City is conducted, and the optimal configuration scheme for energy storage in the region is obtained, verifying the effectiveness and superiority of the proposed energy storage location and capacity configuration method and control strategy. © 2023 Science Press. All rights reserved.
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页码：2744 / 2754
页数：10
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