Optimal dispatch strategy considering fuzzy intention of multi-mode demand response of vehicle owners
DOI：10.19783/j.cnki.pspc.220697
Key Words:master-slave game  EV owner's willingness  multi-mode response  dynamic electricity price
Author NameAffiliation
LI Xianshan 1. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China
2. College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
3. State Grid Yichang Power Supply Company, Yichang 443002, China 
ZHOU Xiaolan 1. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China
2. College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
3. State Grid Yichang Power Supply Company, Yichang 443002, China 
YAO Junwei 1. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China
2. College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
3. State Grid Yichang Power Supply Company, Yichang 443002, China 
XIE Qiongyao 1. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China
2. College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
3. State Grid Yichang Power Supply Company, Yichang 443002, China 
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Abstract: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).
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