A review on optimization scheduling methods of charging and discharging of EV

Abstract

Electric vehicles (EVs) are being introduced by various manufacturers as an environment-friendly alternative to vehicles with internal combustion engines and with some advantages. The quantity of EVs will grow quickly in the coming years. However, the uncoordinated charging of these vehicles can put extreme stress on the power grid. The problem of charge scheduling of EVs is significant and challenging and also has seen significant research over the most recent couple of years. This survey covers the new works done in the area of scheduling algorithms for charging EVs in smart grids. Some heuristic and meta-heuristic algorithmare considered for the real-time charging. EV scheduling method by Genetic Algorithm and Intelligent Scatter Search (ISS) algorithm (GA and ISS), Particle Swarm Optimization (PSO) algorithm, and Reinforcement Learning algorithm(RL) are developed for power loss minimization, electricity cost minimization, peak load reduction. In this point of view interested to propose to integrate fog computing with RL applications deployment in EV charging distributed systems. This integration between fog computing and the RL may have the opportunity to shape the future applications established in the EV charging systems.