Coordinated Dispatching Strategy for Electric Vehicles Considering User Decision‐Making under Spatiotemporal Reconfiguration

With the growing environmental awareness, electric vehicles (EVs), as flexible and mobile load resources, have gradually enhanced their optimization and regulation capabilities in power systems. However, the subjectivity and unpredictability of users' trip plans in special circumstances significantly impact the dispatching results of EV clusters. To address this issue, this paper establishes a real‐time trip chain correction model that integrates power and traffic networks to simulate the distribution of EV charging loads under spatiotemporal reconfiguration. Furthermore, considering the dispatchable potential of EVs after trip completion, a user behavior decision‐making method is proposed. This method utilizes fuzzy control to analyze EV charging demand and quantifies the degree of user responsiveness to the dispatching strategy. Then, based on the charging urgency index, a coordinated dispatching strategy is introduced to mitigate grid fluctuations, reduce peak loads, and lower user charging costs. Finally, experiments analyze the effects of spatiotemporal reconstruction and decision‐making behavior on the EV dispatching process. Results demonstrate the effectiveness of the proposed strategy in reducing users' charging costs while achieving peak load reduction and valley filling in the power grid.