Customer segmentation and value evaluation method based on data mining for electric vehicles
DOI：10.7667/PSPC171615
Key Words:electric vehicle  customer segmentation  data mining  K-MEANS algorithm  customer value evaluation
Author NameAffiliation
ZHANG Lu Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China 
LI Guochang Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China 
CHEN Yanxia Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China 
SUN Zhou Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China 
WANG Weixian Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China 
TIAN Heping Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China 
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Abstract:Customer segmentation is of great significance for charge service operators to obtain the features of charging behaviors and individual differences between various Electric Vehicle (EV) users. Based on large numbers of charging service data fast accumulated by operations management system, exploratory data analysis is applied to all the historical data in the database. Firstly key variables are screened out to the segmentation model, and then the EV customer segmentation method by data mining technique and K-MEANS algorithm is presented. Secondly the customer value evaluation method is proposed, and charging behavioral features and customer values are analyzed based on Beijing EV customers. At last, conclusions and suggestions are given, which would provide data supports for the improvement of operation and maintenance management and decision-making of the precision marketing. This work is supported by Science and Technology Project of State Grid Corporation of China (No. 52020116000J).
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