电力系统保护与控制2025，Vol.53Issue(17)：1-12,12.DOI:10.19783/j.cnki.pspc.241531
计及三相不平衡的电动汽车充电站参与调压辅助服务模型
Voltage regulation ancillary service model for electric vehicle charging station considering three-phase unbalance
摘要
Abstract
Exploring and utilizing the reactive power support capabilities of electric vehicle charging stations can optimize distribution network operation and help mitigate voltage limit violations caused by three-phase unbalances in load,line parameters,and new energy output.Additionally,it can reduce voltage regulation costs for the grid.Hence,this paper proposes a voltage regulation ancillary service model for electric vehicle charging stations while considering three-phase unbalance.First,based on an analysis of the market mechanism for voltage regulation ancillary services and the charging behavior of electric vehicles,the daily load curves of slow and fast charging stations are predicted separately,and their respective reactive power support capabilities are evaluated.Second,a multi-time-scale day-ahead and intra-day optimization framework for distribution networks is established.The day-ahead optimization model aims to minimize the voltage regulation costs of the distribution network,determining the on-load tap changer positions and the scheduling of capacitor banks.The intra-day rolling optimization focuses on minimizing network losses and compensation costs of charging stations by adjusting their reactive power participation in voltage regulation ancillary services.Finally,simulations on the IEEE33-bus system are conducted and the results show that the proposed model can effectively reduce both three-phase voltage unbalance and voltage regulation costs in the distribution network.关键词
充电站/调压辅助服务/三相不平衡/拉丁超立方抽样/滚动优化/日前-日内优化Key words
charging station/voltage regulation ancillary service/three-phase unbalance/Latin hypercube sampling/rolling optimization/day-ahead and intra-day optimization引用本文复制引用
朱晗,汪隆君,陈志峰,王钢..计及三相不平衡的电动汽车充电站参与调压辅助服务模型[J].电力系统保护与控制,2025,53(17):1-12,12.基金项目
This work is supported by the National Natural Science Foundation of China(No.51307063). 国家自然科学基金项目资助(51307063) （No.51307063）
广东省基础与应用基础研究基金项目资助(2023A1515011035) （2023A1515011035）
