“人-车-桩-路-网”深度耦合下的配电网协同规划与运行优化

电动汽车(EV)作为连接交通电气化和电网清洁化的纽带和桥梁，可实现电力-交通-信息之间的深度耦合，形成电力-交通一体化的规划及运行架构。配电-交通融合系统(DTIS)中，EV充放电行为多时空动态交织、电能流-交通流-信息流深度融合、多利益主体动态博弈等大量不确定性因素使配电网的规划及运行优化的边界都将发生重大转变，但同时也给挖掘利用EV的移动储能特性和提升配电网灵活性带来了契机。为此，在分析“人-车-桩-路-网”深度耦合下配电网的形态演化特征基础上，剖析了新形态下配电网协同规划与运行优化所面临的新挑战，进而针对“人-车-桩-路-网”耦合下的EV灵活性建模、灵活域高效构建及预测、协同规划、运行优化4个方面关键技术展开讨论，并对相关技术问题的研究方向进行了展望。

Collaborative Planning and Operation Optimization of Distribution Networks Under Deep Coupling of Drivers, Vehicles, Piles, Traffic and Networks

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.