Multi‐objective optimal planning of EV charging stations and renewable energy resources for smart microgrids. Issue 3 (30th December 2022)

• Record Type: Journal Article
• Authors: Asaad, Ali; Ali, Abdelfatah; Mahmoud, Karar; Shaaban, Mostafa F.; Lehtonen, Matti; Kassem, Ahmed M.; Ebeed, Mohamed
• Is Part Of: Energy science & engineering. Volume 11:Issue 3(2023)
• Page Start: 1202
• Page End: 1218
• Publication Date: 2022-12-30
• Subjects: charging stations -- electric vehicles -- microgrids -- optimization -- renewable energy resources; Energy industries -- Periodicals; Energy development -- Periodicals; Power resources -- Periodicals; 621.042
• DOI: 10.1002/ese3.1385
• Languages: English
• ISSNs: 2050-0505

Abstract

Abstract: Distribution system planners and operators have increasingly exposed great attention to maximizing the penetration of renewable energy resources (RERs), and electric vehicles (EVs) toward modern microgrids. Accordingly, intensive operational and economic problems are expected in such microgrids. Specifically, the operators need to meet the increased demand for EVs and increase the dependence on RERs. The charging strategy for EVs and the RER penetration level may result in increased power loss, thermal loading, voltage deviation, and overall system cost. To address these concerns, this paper proposed an optimal planning approach for allocating EV charging stations with controllable charging and hybrid RERs within multi‐microgrids, where the charging strategy in the proposed planning approach contributed to improving power quality and overall system cost, where the voltage deviation, energy not supplied, total cost have been reduced to 26.03%, 49.57%, and 70.45%, respectively. The simulation results are compared with different optimization techniques to verify the effectiveness of the proposed algorithm. The proposed simultaneous allocation approach of EV charging stations and RERs can reduce operating costs for RERs and conventional stations while increasing the charging stations' capacity. Abstract : This paper proposes an optimal planning approach for allocating electric vehicle (EV) charging stations with controllable charging and hybrid renewable energy resources (RERs) within multi‐microgrids. For this purpose, a multi‐objective function is developed to allocate EV charging stations and RERs, reduce energy not supplied, voltage deviation, and overall system cost using a developed meta‐heuristic algorithm. Compared to previous planning approaches, the suggested planning model stands out for its potential to improve microgrids by simultaneously optimizing the various control variables of RERs and EVs.