A Spatio-Temporal Optimization Strategy for Large-Scale Electric Vehicle Charging and Discharging Considering Wind-Solar-Mobile Power Storage Complementarity

The rapid development of high-penetration renewable energy integration, particularly from wind and solar sources, coupled with the grid connection of a high proportion of electric vehicles (EVs), poses significant challenges to the secure and economic operation of power grids. The unordered charging behavior of EVs may lead to localized overloading, thereby exacerbating the operational pressure on the grid. In response to this issue, this study proposes a spatial-temporal two-layer optimal dispatch strategy for large-scale EV charging and discharging, considering the complementarity between renewable energy and mobile energy storage. This strategy aims to achieve synergistic optimization between EVs and renewable energy generation. The upper-layer dispatch focuses on minimizing generation costs, CO2 emissions, charging expenses, and wind curtailment by optimizing the optimal unit commitment. The lower-layer dispatch, meanwhile, targets minimizing network losses while considering cybersecurity constraints and the spatial migration characteristics of EVs, formulating a dispatch model based on optimal power flow. Simulation results based on the IEEE-33-bus distribution network validate the effectiveness and superiority of the proposed strategy.