电气技术2025，Vol.26Issue(3)：7-14,8.
基于电网脆弱性评估的储能规划选址研究
Research on energy storage site selection based on power grid vulnerability assessment
摘要
Abstract
Against the backdrop of the continuous development of new power system,various regions across the country are actively carrying out new energy storage construction to enhance the regulation capacity of the power system and meet the peak shaving and demand of the power grid.With the characteristics of bidirectional transmission and fast response speed,it is a key issue that should be considered in the site selection stage of energy storage planning,which involves how to effectively improve the security of the power grid and enhance the ability to resist the impact of faults after the new energy storage is access to the power system.A multi-objective decision-making model for energy storage site selection is constructed to address the impact of new energy storage access on the vulnerability of partitioned power grids.Faced with the shortcomings of traditional power grid vulnerability analysis methods,a new vulnerability assessment method based on k-core decomposition is proposed.The system vulnerability indicators under different typical operation scenarios after energy storage access to the power grid are taken as decision-making sub-targets,and the technique for order preference by similarity to an ideal solution(TOPSIS)decision method is used to comprehensively evaluate the optimal solution of energy storage target access point.The rationality and effectiveness of the proposed vulnerability assessment method and the energy storage site selection method are verified through the analysis of the IEEE 39-node system.关键词
储能选址/电网脆弱性/k-核分解/典型运行场景/逼近理想解排序法(TOPSIS)多目标决策Key words
energy storage site selection/power grid vulnerability/k-core decomposition/typical operation scenario/technique for order preference by similarity to an ideal solution(TOPSIS)multi-objective decision-making引用本文复制引用
孙顺祥,李金科,甄宏宁,杨赟,韩志锟..基于电网脆弱性评估的储能规划选址研究[J].电气技术,2025,26(3):7-14,8.基金项目
江苏省基础研究计划(自然科学基金)项目(BK20210048) （自然科学基金）
