Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration

Jin-peng Liu, Teng-xi Zhang, Jiang Zhu and Tian-nan Ma

Energy, 2018, vol. 164, issue C, 560-574

Abstract: Under the background of large-scale electric vehicle (EV) development, it is necessary to design and deploy the EVCS more scientific. Among various factors influential to the EVCS allocation, charging satisfaction and distributed renewables integration were mainly considered in this paper. First, with System Dynamics (SD) model, the key factors affecting the EVCS allocation were identified from the conduction mechanism. Then, focusing on the site selection of EVCS from the aspect of user satisfaction, k-means clustering method was used to illustrate the relationship between charging distance and satisfaction degree. On this basis, considering with renewables integration and stable operation of power system, the paper constructed a multi-objective function including voltage fluctuation, load fluctuation and connected capacity of energy storage in EVCS. Third, under the feeder framework of an IEEE 33-node, GA-PSO was employed to determine the best solution of EVCS allocation., i.e. the optimal allocation number of EVCS, the site and capacity of EVCS, and the access nodes of renewables and EVCS. Combing with the analysis results, suggestions from the aspects of technology standard, finance subsidy, land use support and energy management were proposed for accelerating the generalization of EVs and strengthening the supporting infrastructure construction.

Keywords: Multi-objective optimization; EVCS; Distributed renewables; Charging satisfaction; k-means; GA-PSO (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:164:y:2018:i:c:p:560-574

DOI: 10.1016/j.energy.2018.09.028

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