Adjustable resource assessment and optimal scheduling method for electric vehicles considering cross-station mutual aid

Abstract Electric vehicles (EVs), as a new type of dispatchable resource in distribution networks, can help local new energy consumption and enhance grid security. In this paper, a method for evaluating and optimizing the dispatching of adjustable resources of electric vehicles considering cross-station mutual aid is proposed. Firstly, a Long Short-Term Memory (LSTM) network model is used to predict the power demand of charging posts and the number of Evs, then a consumer psychology model is constructed to evaluate the adjustable resources of EVs by considering the extra time and cost factors of cross-station charging. Then a scheduling model considering cross-station support for EVs is built. Through the case study, the effectiveness of the method in guaranteeing grid security and enhancing the level of new energy consumption is verified.