Integrating Incentive Factors in the Optimization for Bidirectional Charging of Electric Vehicles

Vehicle-to-grid (V2G) technologies can actively integrate electric vehicles (EVs) into power systems, thus playing a crucial role in stabilizing the grid and facilitating seamless integration of intermittent renewable energy. This paper for the first time quantifies and integrates incentive factors into V2G management for realizing efficient, economical, and comfortable EV smart charging. A multi-element V2G incentive analysis model is established by analyzing grid power balancing requirements, considering vehicle charging costs, ancillary service benefits, battery aging, and range anxieties. The established model serves as a useful tool for quantitatively evaluating the incentive effect on V2G from both the grid operator and prosumer sides. Incentivized EV charging management is realized by a hybrid discrete-continuous policy network, where both vehicle charging state transition and power variation are fully controlled for reducing battery aging and maximizing V2G benefits. Charging management of EVs is realized by better balancing the cost-benefit tradeoff between different incentive factors. The effectiveness of the developed method is verified on a practical UK power grid. This research contributes to economical and computationally efficient solutions for managing smart EV charging, benefiting EV owners, network operators, and renewables.