中国电力2026，Vol.59Issue(2)：104-113,10.DOI:10.11930/j.issn.1004-9649.202504013
基于数据驱动的高渗透率电动汽车充电规划与优化
Data driven planning and optimization of high penetration electric vehicle charging
摘要
Abstract
In the context of"double high"penetration of renewable energy and electric vehicles,the uncertainty of power grid supply and demand has significantly increased,urgently demanding planning and scheduling strategies to ensure stable operation.To address this,a data-driven multi-source fusion method is proposed to construct a charging demand prediction model,achieving joint optimization of facility layout and dynamic charging and discharging strategies.The Open Distribution System Simulator(OpenDSS)platform is used as a carrier to model and simulate a typical distribution network.results show that the proposed method can effectively reduce the peak-valley difference of the power grid,enhance the stability of power grid operation and the utilization rate of charging facilities,reduce user charging waiting time.关键词
电动汽车/高渗透率/充电需求预测Key words
electric vehicles/high penetration rate/charging demand forecast引用本文复制引用
戚成飞,王亚超,李文文,张炜,赵鹏..基于数据驱动的高渗透率电动汽车充电规划与优化[J].中国电力,2026,59(2):104-113,10.基金项目
This work is supported by National Natural Science Foundation of China(No.52077012). 国家自然科学基金资助项目(52077012). （No.52077012）
