现代电力2026，Vol.43Issue(1)：72-80,9.DOI:10.19725/j.cnki.1007-2322.2023.0410
基于线损敏感度的配电网BESS二阶段优化配置模型
A Two-stage Configuration Optimization Model for BESS in Distribution Networks Based on Line Loss Sensitivity
摘要
Abstract
The development of photovoltaics(PV)and electric vehicles(EV)has intensified the operational pressure of the distribution network.Although the integration of battery energy storage systems(BESS)can alleviate this situation,existing configuration optimization models rarely consider the impact of BESS integration location on line loss.To address this issue,in this paper we propose a two-stage configuration optimization model for BESS based on line loss sensitivity in distribution networks with high proportions of PV and EV.The first step involves the construction of a BESS access location optimal selection model based on line loss sensitivity.Afterwards,in terms of BESS access capacity optimization,a capacity optimization model is established considering objectives such as operation and maintenance costs,line losses,voltage regulation,and peak load.Moreover,we propose an improved particle swarm optimization algorithm to optimize and solve the model.The proposed method is evaluated on an IEEE-33 node distribution network with a high proportion of PV-EV.The results obtained by the considered algorithms are compared in terms of objective function,system efficiency improvement,investment payback period,and statistical analysis.The simulation results demonstrate that the two-stage configuration optimization for BESS in high proportion PV-EV distribution network based on line loss sensitivity model can effectively reduce line loss,improve voltage distribution,and reduce system cost by 40.05％,line loss by 10.67％,and load peak by 12.05％,thereby verifying the effectiveness of the proposed method.关键词
储能/光伏/配电网/电动汽车/优化配置Key words
energy storage/photovoltaics(PV)/distribution network/electric vehicles/configuration optimization分类
信息技术与安全科学引用本文复制引用
王彬,王学军,葛磊蛟,刘航旭,魏联滨,王莹..基于线损敏感度的配电网BESS二阶段优化配置模型[J].现代电力,2026,43(1):72-80,9.基金项目
国家自然科学基金项目(52277118).Project Supported by National Natural Science Foundation of China(52277118). （52277118）
