An intelligent scatter search (ISS) algorithm for scheduling of charging a single EV

Electric vehicles (EVs) becomes popular for energy saving and environmental protection in light of sustainable development in recent years. The wide spread popularity of EVs relies on an effective strategy for charging the battery. Hence, efficient and robust algorithms are essential for implementing the charging strategies. In this paper, an intelligent scatter search (ISS) framework utilizing filter-SQP (sequential quadratic programming) and mixed-integer SQP techniques as local solvers is proposed for handling EV charging with either flexible or constant charging power under both V2G and G2V support. Simulations have been carried out to verify the effectiveness of the proposed ISS algorithm. The results demonstrated that its performance is better than other approaches including GS (global search), GA (genetic algorithm), PSO (particle swarm optimization), and SS/F (scatter search algorithm with local solver fmincon). In addition, its computational load is rather low in regulating the EV charging and thus is very suitable to minimize the operation cost for EV owners.