Combined analytic hierarchy process and binary particle swarm optimization for multiobjective plug-in electric vehicles charging coordination with time-of-use tarif

Abstract

Plug-in electric vehicles (PEVs) are gaining popularity as an alternative vehicle in the past few years. Thecharging activities of PEVs impose extra electrical load on residential distribution system as well as increasing operationalcost. There are multiple conflicting requirements and constraints during the charging activities. Therefore, this paperpresents multiobjective PEV charging coordination based on weighted sum technique to provide simultaneous benefitsto the power utilities and PEV users. The optimization problem of the proposed coordination is solved using binaryparticle swam optimization. The objectives of the coordination are to (i) minimize daily power loss, (ii) maximize powerdelivery to PEV, and (iii) minimize charging cost of PEV considering time-of-use tariff. In order to determine balanceweighting factor for each of these objectives, analytic hierarchy process is applied. By using this approach, the bestresult of charging coordination can be achieved compared to uncoordinated charging. A 23-kV residential distributionsystem with 449-nodes is used to test the proposed approach. From the attained results, it is shown that the proposedmethod is effective in minimizing power loss and cost of charging with safe operation of distribution system.