中国电机工程学报2025，Vol.45Issue(11)：4144-4162,19.DOI:10.13334/j.0258-8013.pcsee.242157
城市电力-交通耦合系统的联合推演与协同优化:研究综述、挑战与展望
Joint Prediction and Coordinated Optimization of Integrated Urban Power Distribution and Transportation Systems:Literature Review,Challenges and Prospects
摘要
Abstract
With the progress of transportation electrification,the uncoordinated travel and charging behaviors of electric vehicles pose significant challenges to the safe and efficient operation of integrated urban power distribution and transportation systems.Leveraging the spatial-temporal shifting flexibility potential of electric vehicles and achieving joint prediction and coordinated optimization of the integrated systems are crucial for ensuring their secure and economical operation.A comprehensive review of the research directions and key issues is conducted first pertaining to joint prediction and coordinated optimization of the integrated systems.Subsequently,related works are systematically presented from three perspectives:analysis and modelling;perception and prediction;coordinated optimization.Moreover,four major research challenges that span the entire process are identified.Finally,from the combined perspective of system integration and interdisciplinary integration,future research opportunities for integrated systems are identified across four dimensions:physical analysis;perception and prediction;policy optimization;performance improvement on robustness and generalization.关键词
电气交通融合与协同/电动汽车/电动营运车队/智能决策/隐私计算/人工智能Key words
electricity-transportation systems integration and coordination/electric vehicle/electric mobility/intelligent decision-making/privacy-preserving computation/artificial intelligence分类
信息技术与安全科学引用本文复制引用
叶宇剑,吴奕之,胡健雄,刘曦木,刘志远,许德智,万剑,杨烨,Goran STRBAC..城市电力-交通耦合系统的联合推演与协同优化:研究综述、挑战与展望[J].中国电机工程学报,2025,45(11):4144-4162,19.基金项目
国家自然科学基金项目(52477083,52207082,62222307) （52477083,52207082,62222307）
江苏省基础研究计划自然科学基金项目(BK20220842).Project Supported by National Natural Science Foundation of China(52477083,52207082,62222307) （BK20220842）
Natural Science Foundation of Jiangsu Province of China(BK20220842). （BK20220842）
