Agent-Based Simulation for Electric Vehicle Aggregators’ Bidding and Pricing Strategy Considering Reserve Provision and EV Response

Emergence of electric vehicle aggregators (EVAs) could significantly improve the interaction between power grid and massive electrical vehicles. The market behavior of EVA is studied, and an agent-based simulation model is proposed for EVAs' bidding and pricing strategy considering reserve provision. The EVA optimizes its bidding prices, charging prices and incentive prices with the objective to maximize total profits gained from charging service and reserve service. The EV agents can adjust their charging schedules in response to the time-of-use charging prices in order to decrease their charging cost. Based on the energyreserve combined market clearing model, the interaction between EVA and EV owners are modelled as a Stackelberg game and simulated using agent-based approach. The numerical analysis proves the feasibility and effectiveness of model proposed.