Large-scale electric vehicle charging coordination for cost-effectiveness and fairness under peak power constraints

Abstract

Electric vehicles (EVs) are merging as a feasible alternative to existing gasoline-based vehicles to mitigate climate change and greenhouse gas emission. As the number of EVs is increasing, uncoordinated large-scale EV charging behaviors may lead to power grid instability, extra electricity fee and cost unfairness among EV owners. In this paper, we propose a large-scale EV charging coordination framework that enhances cost-effectiveness, cost fairness and target state-of-charge (SoC) level satisfaction. A simple and effective scheduling algorithm, called low-price pursuit algorithm (LPPA), is proposed to minimize the charging costs by considering three-level time-of-use (TOU) periods. Under low peak power constraints, LPPA may lead to challenges, such as EVs not being fully charged or overcharged at high-priced periods. To address these challenges, a novel selective extra charging algorithm (SECA) is proposed to identify problematic EVs through future demand forecasting and simulations, providing additional charging to ensure SoC satisfaction as well as cost-effectiveness. By dynamically incorporating LPPA and SECA, the proposed framework achieves the balance between cost-effectiveness and SoC satisfaction. In addition, we evaluate the fairness of charging costs for each EV by introducing individual cost gains as a performance measure. Simulation results show that the proposed framework achieves better performance than existing schemes across various scenarios, including TOU pricings, charging speeds and EV’s battery capacities.