Artificial Intelligence Based Load Scheduling for Plugged in Electric Vehicles in Smart Grid

Abstract

Plugged in Electric Vehicles (PHEV’s) are enormously eco friendly and highly appreciated transportation system in various developed countries. The PHEV’s integration into the conventional grid required significant modifications in order to control load shedding, reducing unit cost, even out peak demands in quest to make a grid reliable. Recent research studies are mainly focusing to counter these issues by employing multi objective optimization techniques. The objective of this method is to reduce demand; energy cost and enhances the presence of PHEV’s for charging and discharging by creating substantial scheduling vector. This research work has proposed split scheduling vector to charge and discharge an EV, to achieve the required results by minimizing peak to average demand ratio (PAR) and generate profit for the owners by decreasing the total energy cost