电力系统自动化2024，Vol.48Issue(7)：169-180,12.DOI:10.7500/AEPS20230731003
融合路网-电网信息的电动汽车充放电行为引导与调控策略
Guidance and Regulation Strategy for Charging and Discharging Behaviors of Electric Vehicles Based on Fusion of Road Network and Power Grid Information
摘要
Abstract
In the context of the rapid development of smart city concepts,the unguided traveling and disorderly charging and discharging behaviors of electric vehicles(EVs)are affecting the safe and efficient operation of the power-transportation coupling network.To address this problem,this paper proposes a two-phase optimal guidance and regulation strategy for charging and discharging behaviors of EVs based on the fusion of road network and power grid information.Firstly,the interactive factors and modes of the power-transportation coupling network are analyzed,and the guidance and regulation architecture of EV charging and discharging travel path are proposed.Secondly,a dynamic updating strategy for the electricity price of EV charging and discharging travel decision is proposed based on the fusion of road network and power grid information,and an optimization model for EV charging and discharging travel path decision-making is established considering the user time-economic cost.Then,the EV charging and discharging regulation model is established considering the interests of multiple stakeholders.Finally,the simulation results show that the proposed strategy can comprehensively consider the real-time operation state of the road network and the power grid,fully tap into the adjustable potential in the process of path guidance and charging and discharging regulation of EVs,and realize the coordinated operation of the system and multi-party win-win.关键词
电动汽车/路网/电力-交通耦合网络/优化引导与调控/动态电价/多利益主体/行为决策Key words
electric vehicle/road network/power-transportation coupling network/optimal guidance and regulation/dynamic electricity price/multiple stakeholders/behavior decision引用本文复制引用
玉少华,杜兆斌,陈丽丹,陈南星,李家乐..融合路网-电网信息的电动汽车充放电行为引导与调控策略[J].电力系统自动化,2024,48(7):169-180,12.基金项目
广东省重点领域研发计划资助项目(2019B111109001). This work is supported by Key Area R&D Program of Guangdong Province(No.2019B111109001). （2019B111109001）
