Leader-Follower Game Optimization Scheduling Strategy for Photovoltaic Energy Storage Charging Stations Considering User Intentions

The leader-follower game between electric vehicles (EVs) and photovoltaic energy storage charging stations (PECS) plays an important role in maximizing the revenue of PECS and reducing user charging costs. However, due to the uncertainty of users' charging behavior strategies, the iteration accuracy of the leader-follower game of PECS is affected. To this end, an optimization scheduling strategy of the leader-follower game between EVs and PECS considering user intention is proposed. The PECS formulates a dynamic electricity price incentive policy for EVs to guide EVs to charge and discharge in an orderly manner. Users establish a three-way decision (T-WD) model based on regret theory (RT) to respond to dynamic electricity prices and obtain EV charging and discharging strategies. The results of the example analysis show that the proposed method can maximize the benefits of the PECS based on the judgment of user intentions.