电力系统自动化2024，Vol.48Issue(7)：62-85,24.DOI:10.7500/AEPS20230731006
信息-物理-社会视角下的电力-交通耦合网络建模与协同优化
Collaborative Modeling and Optimization of Power-Transportation Coupling Network from Cyber-Physical-Social Perspective
摘要
Abstract
In recent years,the rapid growth of electric vehicles(EVs)and fast charging facilities has two closely coupled complex infrastructure networks,which is the power system and transportation system.With flexibility in charging time and location,EVs become ideal mobile energy storage resources for new power systems,which provide massive spatial and temporal flexible regulation capabilities.However,behind the macro power-transportation coupling is the micro social decision-making of numerous EV users under the guidance of the multi-source information,which forms a complex cyber-physical-social system.The relevant research on collaborative modeling and optimization of power-transportation coupling network from such perspective is reviewed.Firstly,the basic scenarios and key challenges of power-transportation network are introduced.Subsequently,focusing on social and physical layers,the modeling of EV traveling-charging behavior is reviewed,which integrates the micro EV user decision-making and macro network dynamics.Then,further incorporating the cyber layer,the strategy interaction and collaborative optimization among multiple pricing entities with EV drivers are summarized.Finally,prospects are made for the research on modeling and the optimization of power-transportation coupling network.关键词
电动汽车/电网/交通网/信息-物理-社会系统/协同优化Key words
electric vehicle/power grid/transportation network/cyber-physical-social system/collaborative optimization引用本文复制引用
盛裕杰,郭庆来,薛屹洵,王嘉炜,常馨月..信息-物理-社会视角下的电力-交通耦合网络建模与协同优化[J].电力系统自动化,2024,48(7):62-85,24.基金项目
国家自然科学基金区域创新发展联合基金资助项目(U22A6007) （U22A6007）
山西省能源互联网研究院研发资助项目(SXEI2023A003). This work is supported by Regional Innovation and Development Joint Fund of National Natural Science Foundation of China(No.U22A6007)and Shanxi Energy Internet Research Institute(No.SXEI2023A003). （SXEI2023A003）
