Electric Vehicle Solar Charging Station Siting Study Based on GIS and Multi-Criteria Decision-Making: A Case Study of China

被引:11
|
作者
Zhao, Hui [1 ]
Gao, Jing [1 ]
Cheng, Xian [1 ]
机构
[1] Qingdao Univ Technol, Sch Management Engn, Qingdao 266520, Peoples R China
基金
中国国家自然科学基金;
关键词
EVs; charging station siting; photovoltaic; GIS; fuzzy DEMATEL; fuzzy MULTIMOORA; INFORMATION-SYSTEMS GIS; OPTIMAL SITE SELECTION; ION BATTERIES; MCDM METHODS; LITHIUM-ION; WIND FARMS; ENERGY; MANAGEMENT; LOCATION; SCALE;
D O I
10.3390/su151410967
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Electric vehicles (EVs) are one of the most practical solutions to the energy issue and environmental pollution. In recent years, EVs have developed rapidly, but are still limited by charging problems. The emergence of photovoltaic charging stations can solve the environmental pollution and charging problems. The location of charging stations is critical in the life cycle of electric vehicles. In this paper, a multiple-criteria decision-making (MCDM) method based on Geographic Information Technology (GIS) for optimal site selection is proposed. First, based on literature reading and expert interviews, a site selection index system was identified, including four aspects with a total of ten sub-criteria. Secondly, a spatial database of relevant evaluation criteria was established using GIS, and preliminary analysis was conducted. Then, the fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory method) is applied for assigning the criteria weights. Then, potential sites are ranked using the fuzzy MULTIMOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method. Then, the model was validated by siting the electric vehicle PV charging stations in Qingdao, and eight stations were identified in the preliminary selection stage, and the most suitable locations were finally selected through the MCDM stage. Finally, the reliability and validity of the model were further verified by comparative analysis and dual sensitivity analysis.
引用
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页数:23
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