Optimal V2G and G2V Operation of Electric Vehicles using Binary Hybrid Particle Swarm Optimization and Gravitational Search Algorithm

Abstract

The smart grid paradigm enables improved participation of customers in operational aspects of power system. The optimal charge-discharge operation of electric vehicles (EV) is one of the means for improvising such customer participation. Therefore, this paper presents a hybrid meta heuristic approach using particle swarm optimization and gravitational search algorithm for optimal charge-discharge event management of EVs in smart grid. The same is carried out in conjunction with the unit commitment procedure of power system operation. The UC problem belongs to the class of binary optimization problems where the search space is constricted to binary digits. For this, the real valued optimization variables and process is mapped to binary version using tangent hyperbolic transformation. The effectiveness of BHPSO-GSA is examined through extensive numerical experiments on various scenarios. The simulation results are presented, discussed and compared to other existing approaches to demonstrate the superiority of proposed approach in solving UC problem with and without EV in smart grid.