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

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.

Proposed Ranked Strategy for Technical and Economical Enhancement of EVs Charging With High Penetration Level

“…In addition, [26], [27], and [33] did discuss the charging cost reduction issue in their strategies which are considered a vital concern. In [32], the charging cost reduction has reached 22.4%, which is less than the proposed strategy by 17.7%.…”

“…Table 5 illustrates a comparison between the proposed strategy AR-IFC and other strategies in some research studies on the same tested system. These four studies in [26], [27], [32], and [33] have been chosen for a fair comparison as they are recent research that investigated the optimal charging of EVs without implementing any renewable resources. The studies applied different charging techniques, [27], [32], and [33] use fixed charging techniques, while [26] use variable charging techniques.…”

“…These four studies in [26], [27], [32], and [33] have been chosen for a fair comparison as they are recent research that investigated the optimal charging of EVs without implementing any renewable resources. The studies applied different charging techniques, [27], [32], and [33] use fixed charging techniques, while [26] use variable charging techniques. Besides, the variety in their implemented objective functions, where [26] and [33] applied a single objective, but [27] and [32] implemented a double objective function.…”

“…The studies applied different charging techniques, [27], [32], and [33] use fixed charging techniques, while [26] use variable charging techniques. Besides, the variety in their implemented objective functions, where [26] and [33] applied a single objective, but [27] and [32] implemented a double objective function. The results the effectiveness of the proposed strategy where both the peak consumed power and the peak power are the least among other researches, although they have implemented more advanced optimization techniques.…”

Smart charging of electric vehicles to minimize the cost of charging and the rate of transformer aging in a residential distribution network

“…SC schemes that minimize voltage deviations in the network have also been developed [14,15]. In addition to these technical objectives, SC may also seek to minimize the utility's generation costs [16,17] or the EV owners' charging cost [18,19]. The bidirectional communication and smart metering that are indispensable for the above SC strategies require significant capital outlay.…”