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Study of site selection of electric vehicle charging station based on extended GRP method under picture fuzzy environment

机译:图像模糊环境下基于扩展GRP方法的电动汽车充电站选址研究

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Electric vehicle charging station (EVCS) site selection problem plays an important role in promoting electric vehicle industry development. The purpose of EVCS site selection is to find optimal location considering some conflicting criteria. To handle the uncertainty of information in EVCS site selection problem, the picture fuzzy set (PFS) is a good choice, which is characterized by three functions: the degree of positive membership, the degree of neutral membership and the degree of negative membership. In this paper, an effective comprehensive framework is proposed to evaluate and select the optimal EVCS site under picture fuzzy environment. Firstly, from the perspective of sustainability, some main criteria and corresponding sub-criteria are determined by reference to the existing literature and experiences of experts. Secondly, some operational laws of picture fuzzy numbers (PFNs) are defined and the picture fuzzy weighted interaction geometric (PFWIG) operator is developed. Thirdly, fuzzy analytic hierarchy process (FAHP) technique is utilized to determine the weights of criteria and the local weights of corresponding sub-criteria before comprehensive picture fuzzy decision matrix is further constructed based on the developed PFWIG operator. Afterwards, the traditional grey relational projection (GRP) method is extended to calculate the relative grey relational projection of each EVCS site. Thus, all EVCS sites are ranked and the most desirable one(s) can be selected. Finally, an empirical example about EVCS site selection in Beijing is given to illustrate the application of the proposed framework. The results indicate that the proposed framework is useful for identifying suitable EVCS site among the potential charging stations.
机译:电动汽车充电站(EVCS)选址问题在促进电动汽车产业发展中起着重要作用。 EVCS站点选择的目的是在考虑一些冲突标准的情况下找到最佳位置。为了处理EVCS选址问题中的信息不确定性,图片模糊集(PFS)是一个不错的选择,它具有三个功能:正隶属度,中性隶属度和负隶属度。本文提出了一个有效的综合框架,用于在图像模糊环境下评估和选择最佳EVCS站点。首先,从可持续性的角度出发,参考现有文献和专家经验确定一些主要标准和相应的子标准。其次,定义了图片模糊数(PFNs)的一些运算规律,并开发了图片模糊加权交互几何(PFWIG)算子。第三,在基于已开发的PFWIG算子进一步构造综合图片模糊决策矩阵之前,利用模糊层次分析法确定准则的权重和相应子准则的局部权重。之后,扩展了传统的灰色关联投影(GRP)方法,以计算每个EVCS站点的相对灰色关联投影。因此,对所有EVCS站点进行排名,并可以选择最理想的站点。最后,以北京EVCS选址为例,说明了该框架的应用。结果表明,提出的框架对于在潜在的充电站中识别合适的EVCS站点很有用。

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