Based on regional integrated energy automatic demand response optimization scheduling of electric vehicle

Abstract

Abstract Regional integrated energy system research is the current trend of energy development. Electric vehicle is an important part of the integrated energy system. Electric vehicle can realize the optimal allocation of energy by participating in automatic demand response (ADR). Therefore, this paper proposes based on regional integrated energy automatic demand response optimization scheduling of electric vehicle with based on the conditional value at risk with the utility function (UCVaR-based) electric vehicle response intention decision model under integrated energy system. Primarily, given both the electric vehicle’s advantage and the network load fluctuation, a based on regional integrated energy automatic demand response optimization scheduling of electric vehicle model is proposed. The price-based DR stage aims to minimize the charge/discharge cost. Minimizing the gap at the incentive-based demand response stage between the peak and valley load. Then, to quantify the risk attitude of an EV group, the UCVaR-based EV owner response willingness decision model is adopted. Specifically, prospect theory is used to calculate the utility value of electric vehicle owners. Finally, to check the feasibility of the proposed process, a case study is given. Results show that compared to the price-based demand response model, the model, which is proposed in this paper, decreased the average charging expense of electric vehicles by 49 percent and raised the gain by 19 percent.