Aggregation Model of Distributed Resources Considering Electric Vehicle Demand Response

As electric vehicles (EVs) are integrated into the power grid on a large scale, their uncoordinated charging further exacerbates the peak-to-valley differences in grid load. By aggregating EVs with other distributed resources, they can serve as demand-side resources with significant scheduling potential, meeting market access thresholds. Therefore, this paper proposes a distributed resource aggregation model that considers the response willingness of EVs, depicting the impact on the power output of aggregated distributed resources after EVs participate in demand response. Initially, based on multiple factors such as the state of charge and charging prices of EVs, their response willingness is quantified using a fuzzy model. Subsequently, considering the uncertainty of EV response, an assessment model for the response potential of EVs is established to determine the dispatchable margin of EV groups participating in demand response. Finally, various distributed resources are aggregated into a virtual power plant (VPP) optimization model for the day-ahead stage to obtain its external equivalent model and cost function facing higher-level dispatching requirements, assessing its peak-shaving capacity. Simulation results demonstrate the effectiveness and feasibility of the model.