电力系统自动化2024，Vol.48Issue(7)：24-37,14.DOI:10.7500/AEPS20231023002
"人-车-桩-路-网"深度耦合下的配电网协同规划与运行优化
Collaborative Planning and Operation Optimization of Distribution Networks Under Deep Coupling of Drivers,Vehicles,Piles,Traffic and Networks
摘要
Abstract
Electric vehicles(EVs),as a link and bridge connecting transportation electrification and grid cleanliness,can achieve deep coupling among electricity,transportation and information,forming an integrated planning and operation architecture of electricity and transportation.In the distribution-transportation integrated system(DTIS),a large number of uncertain factors such as the multiple spatio-temporal dynamic interweaving of EV charging and discharging behaviors,deep integration of electricity flow,traffic flow and information flow,and dynamic game among multiple stakeholders will cause significant changes in the planning and operation optimization boundaries of the distribution network.However,at the same time,it also brings opportunities to explore and utilize the mobile energy storage characteristics of EVs and improve the flexibility of the distribution network.Therefore,based on the analysis of the morphological evolution characteristics of the distribution network under the deep coupling of drivers,vehicles,piles,traffic and networks,the new challenges faced by the collaborative planning and operation optimization of the distribution network in the new form are analyzed.Furthermore,four key technologies such as EV flexibility modeling,efficient construction and prediction of flexible regions,collaborative planning,and operation optimization under the coupling of drivers,vehicles,piles,traffic and networks are discussed,and the research directions of the related technical issues are prospected.关键词
电动汽车/电力-交通一体化/协同规划/运行优化/灵活域/多模态信息融合Key words
electric vehicle/integration of power and transportation/collaborative planning/operation optimization/flexibility region/multi-mode information fusion引用本文复制引用
穆云飞,金尚婷,赵康宁,董晓红,贾宏杰,戚艳.."人-车-桩-路-网"深度耦合下的配电网协同规划与运行优化[J].电力系统自动化,2024,48(7):24-37,14.基金项目
国家自然科学基金联合基金资助项目(U22B20105) （U22B20105）
国家自然科学基金优秀青年科学基金资助项目(52222704). This work is supported by National Natural Science Foundation of China(No.U22B20105,No.52222704). （52222704）
