Optimal Scheduling of Electric Vehicle Clusters Considering Uncertainty of User Demand Response

There is a large uncertainty in the participation of electric vehicle (EV) users in demand response, which brings great challenges to the optimal scheduling of EVs, this paper proposes an optimal scheduling method for EV clusters is response to this issue. Firstly, the uncertainty of user demand response is described by the number of intervals, and the EV user demand response model is established. Secondly, the fuzzy C-means clustering method is used to cluster the EVs connected to the power grid, and the energy boundary model of the EV cluster is established. After that, an optimal scheduling model for EV clusters is constructed that takes into account the uncertainty of user demand response, with the goal of minimizing the variance of regional load fluctuation and maximizing the benefits of the aggregator. Finally, the effectiveness of the proposed method model is verified by actual examples, and the results show that the model can effectively reduce the variance of load fluctuations in the region and the scheduling cost of EV.