Assessment method of electric vehicle schedulable potential and optimal dispatch strategy considering V2G

In the context of rapid electric vehicles (EVs) growth and the development of vehicle-to-grid (V2G) technology, accurately assessing their dispatchable potential and implementing cost-effective charging and discharging optimization are key to leveraging the advantages of EVs as distributed energy storage. To address this, an assessment method of electric vehicle schedulable potential and optimal dispatch strategy considering V2G is proposed. First, based on the nonhomogeneous Poisson process assumption and Sequential Monte Carlo method, EV queuing and charging scenarios are simulated. Through analyzing the feasible regions of EV dispatchable capacity under both charging and V2G scenarios, the dispatchable power capacity of EV aggregators is calculated. Secondly, based on the analysis of the management framework for EVs participating in power dispatch and considering the interaction between electric vehicles and the power grid, an optimal dispatch model for EV clusters has been established. By incorporating multiple optimization objectives such as aggregator profits, charging economy, and peak load reduction, this model facilitates the orderly scheduling of EVs while ensuring secure and economical grid operation. Finally, a practical case study is used to verify the proposed model and algorithm.