A Heuristic Schedule of plug-in electric vehicles (PEV) in order to reduce the active power losses considering the state of charge (SOC) factor

Nowadays, with the widespread adoption of plug-in electric vehicles (PEVs), an efficient coordination among load generation, transmission, distribution, and customers is expected. This paper presents a novel approach to coordinate the PEVs’ scheduling plan to reduce the total amount of active power losses. To close a gap between reality and simulation, the traveling time of the PEV is considered throughout the problem modeling. Also, a prominent factor of the PEV called state of charge (SOC) is considered as a constraint of PEV. To achieve the best result in the scheduling of PEVs, the binary particle swarm optimization is used. Further, the case study is evaluated in different scenarios, concerning the existence of vehicle to grid technology (V2G), and the load variation of the system

Keywords:

Plug-in Hybrid Electric Vehicle , State of Charge , Power Loss , Binary Particle Swarm Optimization