Aggregator-Electric Vehicle Day-ahead Trading Mechanism and Scheduling Strategy Based on Master-Slave Game

EV aggregators guide EVs to participate in dispatching which is essentially a demand response process. However, the research on traditional tariff trading mechanism lacks in-depth consideration of users’ differentiated charging laws and demand characteristics. To address this problem, this paper proposes a master-slave game-based station aggregator-electric vehicle day-ahead contract trading mechanism model. Firstly, a tariff contract trading mechanism considering differentiated contract scheduling periods is designed in the day-ahead phase, a master-slave game model is constructed between the aggregator and the EV fleet, an upper-level aggregator pricing optimization model is established with the goal of maximizing the operational net income, and a lower-level EV charging and discharging scheduling model is established with the goal of maximizing the consumer’s residual, so that the charging and discharging can be guided in an orderly way, and finally, a master-slave game model is constructed in the station with the adoption of the IGA-YALMIP/CPLEX solver joint solution. The algorithm proves that the proposed contract trading mechanism can realize the win-win economic benefits for both aggregators and EVs, and improve the shortcomings of the current scheduling mechanism by the contract trading mechanism in the past few days to realize vehicle-specific solutions.