As a typical dispatchable flexible load, electric vehicles’ (EVs) individual controllable power is low, easy to be affected by user behavior, and have a certain randomness, which are difficult to be controlled by conventional power grid regulation method. In order to make full use of the potential of EVs participating in power grid ancillary services, reduce the impact of plug-in-EVs on the power grid, improve the power grid operation level and guarantee the benefits of EV users, this paper proposes a daily multi-objective optimal regulation strategy for EVs participating in peak shaving ancillary services based on the consideration of EVs’ dispatchable capacity. Firstly, EVs dispatchable capacity is evaluated based on controllability of EVs, and then the multi-objective optimization algorithm NSGA-II is used to solve the optimization model, and the grid dispatching instruction is decomposed into EV subgroup dispatching instruction. Finally, the EV subgroup charging scenario is set up and an example simulation is carried out to verify the effectiveness and accuracy of the proposed method.

electric vehicle,multi-objective optimization,instruction decomposition,dispatchable capacity