Reliability-Oriented Optimization Scheduling Strategy for Electric Vehicle Charging and Discharging Considering Users' Fuzzy Intentions

In addressing the distribution grid overload resulting from the extensive integration of electric vehicles (EVs) for charging, and to efficiently manage the flexible charging and discharging characteristics of EVs while considering the uncertainty in EV users' participation willingness, a price-incentive demand response-based EVs Charging and Discharging Optimization Scheduling model is proposed. Firstly, considering factors such as the owner's time anxiety level and charging cost, EV users' participation willingness is quantified through fuzzy logic inference. Secondly, based on the duration of the owner's stay, combined with price-based and incentive-based demand response measures, more comprehensive charging and discharging options are provided for EVs. Next, a pricing-incentive EVs charging and discharging scheduling model is established, aiming to minimize net load fluctuation on the grid side and minimize charging costs on the user side, considering system reliability and fully exploiting the flexibility characteristics of EVs. Finally, the effectiveness of the proposed model and method is validated through simulation.