An Efficient Scheduling Scheme for Plug-In Electric Vehicles

Abstract

Plug-in electric vehicles (PEVs) will significantly impact the power system due to their interactions with the grid. Grid to Vehicle (G2V) and Vehicle to Grid (V2G) transactions can happen between PEVs and the grid. In order to overcome the impact of charging and discharging of PEV s,’ an intelligent scheduling scheme is essential. This work proposes two optimum scheduling techniques for PEV G2V and V2G transactions, namely, a locally optimum scheduling strategy as well as an equitable distribution strategy. An effective scheduling strategy is developed by first formulating a local scheduling optimization issue, which intends to reduce the overall cost of the EVs in the current EV fleet of the local group. The particle swarm optimization (PSO) algorithm is used to solve the optimization problem. The locally optimal scheduling scheme is not only able to handle a large number of EVs but also to handle random arrivals of EVs. In addition, an approach for equitable distribution strategy is suggested for comparison with a locally optimal scheduling. It is found that the equitable distribution method efficiently handles an enormous fleet of PEVs. Furthermore, the equitable distribution technique is observed to work well in handling multiple PEVs. Simulated outcome verify the efficacy of the proposed scheme.