Multi-agent Day-ahead Bidding Strategy of Electric Vehicle Aggregators Upon Demand Response Potential

Aiming at the competition of the multi-agent market under the mass access of electric vehicles, which are a new energy storage resource, a multi-agent day-ahead bidding strategy for electric vehicle aggregators with demand response potential is proposed. The proposed strategy is to explore the future business model, to achieve the goal of peak reduction and valley filling, ensure the safe and stable operation of the power grid, and promote the sustainable development of the multi-agent market. First, cluster classification is carried out according to the travel characteristics of EV users, factors such as travel time, arrival time, and state of charge are used to simulate the charging and discharging choice of users in the cluster. Based on the historical data, demand response potential is evaluated by combining the power upper limit and power interval value. Second, considering multiple EVA bidding issues, a day-ahead market bidding model is established to calculate the market benefits of operators. Third, with the maximum net profit of day-ahead bidding as the objective function, we consider the constraints of electricity, power ceiling, and battery capacity. To explore the multi-agent day-ahead market strategy, Gurobi is used to solve the optimization problem. Finally, the real-world case studies based on a district in Wuhan, Hubei Province, China verify the effectiveness and merits of the proposed method.