综合智慧能源2026，Vol.48Issue(4)：60-71,12.DOI:10.3969/j.issn.2097-0706.2026.04.007
基于可调度时长预测的电动汽车优化调度研究
Optimal scheduling of electric vehicles based on schedulable duration prediction
摘要
Abstract
With the rapid growth of the number of electric vehicles(EVs),large-scale uncoordinated charging has exacerbated the peak-valley load differences in distribution networks and degraded power quality,making coordinated charging control critically important.However,existing scheduling methods fail to fully consider the uncertainty in EV charging duration and lack targeted prediction mechanisms.Taking the actual charging data provided by ACM Laboratory in the United States as an example,a hierarchical and clustered coordinated charging control method for EVs based on schedulable duration prediction was proposed.The EV charging duration was predicted,serving as the basis for constructing an EV clustering model.Economic optimal scheduling was performed under power balance and energy storage constraints.Then,power flow verification was conducted in the distribution network,with limit violation information fed back to drive closed-loop re-optimization of the charging station.A power allocation algorithm was employed to achieve coordinated charging and discharging control,ensuring both the security and economic efficiency of system operation.Case simulation results demonstrated that the proposed optimal scheduling method effectively captured EV parking patterns and improved prediction accuracy.The load variance of the charging station decreased by 26.55％,effectively lowering EV charging and discharging costs and enhancing system economic performance.关键词
电动汽车/优化调度/有序充电控制/可充电时长预测/分层分群/充放电成本Key words
electric vehicles/optimal scheduling/coordinated charging control/charging duration prediction/hierarchical clustering/charging and discharging cost分类
能源科技引用本文复制引用
彭文河,蔡瑞天,张华英,王化龙,黄欢,吴宜聪..基于可调度时长预测的电动汽车优化调度研究[J].综合智慧能源,2026,48(4):60-71,12.基金项目
中国能源建设集团广西电力设计研究院科技项目(PJ23008)Project of China Energy Engineering Group Guangxi Electric Power Design Institute Company Limited(PJ23008) （PJ23008）
