考虑车主多模式需求响应模糊意愿的优化调度策略

现代电动汽车(electrical vehicle, EV)用户需求响应具有多样性和意愿模糊性的特点，当实施单一激励政策时，EV响应将达不到预期效果。为此，提出了考虑车主多模式需求响应及其模糊意愿的含EV微电网的主从博弈优化调度策略。微电网主体针对净负荷制定多模式动态电价激励政策，引导EV在多模式电价中做出选择，促进EV有序充放电，实现其净负荷均方差和运行成本最小。车主从体基于模糊逻辑推理意愿决策，响应多模式动态电价，极小化车主成本。采用非支配排序遗传算法(NSGA-Ⅱ)求解优化模型，获得最优多模式动态电价和EV充放电策略。仿真结果验证了所提方法的有效性。

Optimal dispatch strategy considering fuzzy intention of multi-mode demand response of vehicle owners

The demand response of modern electric vehicle (EV) users is characterized by diversity and fuzziness of willingness. When a single incentive policy is implemented, the EV response will not achieve the desired effect. Therefore, this paper proposes a master-slave game optimization scheduling strategy for an EV microgrid considering the multi-mode demand response and fuzzy intention of vehicle owners. The main body of the microgrid formulates a multi-mode dynamic electricity price incentive policy for net load, guides the EV to make choices in multi-mode electricity price, and promotes orderly charging and discharging of EV. It also realizes minimum net load mean square deviation and operational cost. Based on the fuzzy logic reasoning willingness decision, the vehicle owner responds to the multi-mode dynamic electricity price to minimize the vehicle owner cost. The NSGA-II algorithm is used to analyse the optimization model to obtain the optimal multi-mode dynamic electricity price and EV charging and discharging strategy. Simulation results verify the effectiveness of the proposed method. This work is supported by the National Natural Science Foundation of China (No. 51607105).