电力系统自动化2026，Vol.50Issue(15)：148-157,10.DOI:10.7500/AEPS20250814007
面向电动汽车精确聚合的充放电模型凸化及约束集内缩方法
Convexification of Charging and Discharging Model and Constraint Set Contraction Method for Accurate Electric Vehicle Aggregation
摘要
Abstract
Massive electric vehicle(EV)aggregation control technology is the key to achieving efficient participation of large-scale EVs in vehicle-to-grid(V2G).However,existing aggregation methods face two major challenges:first,the mutually exclusive characteristics of EV charging and discharging lead to non-convexity in the power feasible region;second,the power constraint boundaries of EVs with different user preferences exhibit significant differences.The former will result in overestimation of the adjustable boundaries of EVs,while the latter makes the evaluation of adjustable boundaries of EVs tend to be conservative.To address the above problems,this paper first achieves convex characterization of the non-convex feasible region by reconstructing the mathematical expression of the EV power feasible region,effectively solving the modeling problem of mutually exclusive charging-discharging constraints.Second,a constraint set contraction based aggregation algorithm is designed,which significantly improves the evaluation accuracy of adjustable boundaries under boundary differences by enhancing the inner approximation degrees of freedom of traditional aggregation algorithms.Case study analysis demonstrates that the proposed method effectively improves the computational efficiency and aggregation accuracy of massive EV scheduling.关键词
电动汽车/车网互动/可行域/闵可夫斯基和/可调边界/聚合Key words
electric vehicle(EV)/vehicle-to-grid(V2G)/feasible region/Minkowski sum/adjustable boundary/aggregation引用本文复制引用
巫子然,余涛,吴毓峰,潘振宁,王克英..面向电动汽车精确聚合的充放电模型凸化及约束集内缩方法[J].电力系统自动化,2026,50(15):148-157,10.基金项目
国家自然科学基金企业创新发展联合基金集成项目(U24B6010) （U24B6010）
广东省基础与应用基础研究基金项目(2025A1515010118). This work is supported by National Natural Science Foundation of China(No.U24B6010)and Guangdong Basic and Applied Basic Research Foundation(No.2025A1515010118). （2025A1515010118）
