Bi-Level Regulation Method of Vehicle-Network Interaction Demand Side Based on Fuzzy Evaluation of Quantum Particle Swarm Optimization

Aiming at the problem of load fluctuation in distribution network caused by large-scale electric vehicle (EV) access, this paper proposes a bi-level control method of vehicle-network interaction demand side based on quantum particle swarm fuzzy evaluation. Firstly, the objective response capability constraint model of users and the subjective response willingness evaluation model considering the incentive level are established, and the response potential of EVs is calculated by combining the objective response capability and the subjective response willingness. Secondly, an incentive real-time demand response bi-level optimization model is established. The upper model optimizes the incentive price of EV aggregators to minimize the incentive cost of EV aggregators, and the lower model optimizes the EV charging and discharging power to maximize the average charging satisfaction of users. Then, the quantum particle swarm optimization algorithm is used to solve the optimization problem. Finally, simulation verifies that the proposed model and method are effective.