Fast charging coordination for electric vehicles in a charging station based on heuristics and metaheuristics

The automotive market is moving fast towards electric vehicles (EV). The ever-growing EV technology and associated service infrastructure, appropriate policies and regulations among other factors are increasing the user's acceptance and confidence in the EV industry, resulting in the growth of EV sales. The existing barriers to the expansion of EV sales such as relatively high purchase prices, the small number of charging stations, uneven distribution of charging stations, and charging times, tend to disappear over time and the expectation is that soon EVs will constitute a significant share of new car sales globally. This work tackles specifically the charging time problem and proposes solutions for coordinating the charging of a group of electric vehicles in a charging station based on the metaheuristic teaching-learning-based optimization (TLBO) and on a specialized heuristic technique. The proposed methods seek to deliver as much energy as possible to vehicles' batteries without violating the constraints and limits of the distribution grid. TLBO is an efficient metaheuristic algorithm that requires few tuning parameters and does not depend on historical data to obtain an optimal solution for an optimization problem. Also, the specialized heuristic technique makes use of specific knowledge about the optimal charging problem to obtain a fast, high-quality solution. Simulation results obtained from the TLBO algorithm are presented alongside those from the heuristic method, with discussions, performance comparisons, and recommendations for practical applications. It will be seen that the proposed approaches are able to meet the efficiency requirement expected by EV customers.