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

Authors : Junaıd Bın Fakhrul ISLAM, Mır Toufıkur RAHMAN, Hazlıe MOKHLIS, Mohamadarıff OTHMAN, Tengku Fıaz Tengku Mohmed Noor IZAM, Hasmaını MOHAMAD

Pages : 1314-1330

Doi:10.3906/elk-1907-189

View : 6 | Download : 6

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :Plug-in electric vehicles PEVs are gaining popularity as an alternative vehicle in the past few years. The charging activities of PEVs impose extra electrical load on residential distribution system as well as increasing operational cost. There are multiple conflicting requirements and constraints during the charging activities. Therefore, this paper presents multiobjective PEV charging coordination based on weighted sum technique to provide simultaneous benefits to the power utilities and PEV users. The optimization problem of the proposed coordination is solved using binary particle swam optimization. The objectives of the coordination are to i minimize daily power loss, ii maximize power delivery to PEV, and iii minimize charging cost of PEV considering time-of-use tariff. In order to determine balance weighting factor for each of these objectives, analytic hierarchy process is applied. By using this approach, the best result of charging coordination can be achieved compared to uncoordinated charging. A 23-kV residential distribution system with 449-nodes is used to test the proposed approach. From the attained results, it is shown that the proposed method is effective in minimizing power loss and cost of charging with safe operation of distribution system.
Keywords : Plug in electric vehicle, charging coordination, analytic hierarchy process, cost minimization, optimization