摘要
随着充电基础服务设施的不断完善,电动汽车用户的充电正逐步扩展到以高速、城市、乡镇、单位和景区等多元化环境,这使得用户的充电行为呈现出明显差异,尤其是在充电成本敏感性方面。基于CRITIC-GMM模型,研究了电动汽车用户在不同充电场景下的充电成本敏感性差异。首先,考虑到充电场景的多元化特征,运用CRITIC方法对充电价格、充电时长、充电时间等关键特征进行客观赋权,确保分析结果的精准性。接着,利用高斯混合模型(GMM)对用户行为进行聚类分析,揭示了不同场景下电动汽车用户充电成本敏感性差异的原因和特点。结果发现,电动汽车用户在乡镇、市区和单位等场景对充电价格较为敏感,通常选择在电价较低时段充电;而在高速公路和景区场景,用户更关注充电效率,充电成本敏感性较低。这一结果为充电设施的差异化定价和提升用户充电体验提供了重要理论依据和实践指导。
With the continuous improvement of charging infrastructure,electric vehicle(EV)users are increasingly charging in diversified environments such as expressways,urban areas,towns,workplaces,and scenic spots.This has led to significant differences in user charging behaviors,particularly regarding cost sensitivity.This paper investigates the differences in charging cost sensitivity among EV users across various scenarios using the CRITIC-GMM model.First,considering the diversity of charging scenarios,the CRITIC(Criteria Importance Through Intercriteria Correlation)method was employed to objectively weight key features—including charging price,charging duration,and charging time—ensuring the accuracy of the analysis.Subsequently,the Gaussian Mixture Model(GMM)was utilized for clustering analysis of user behavior,revealing the causes and characteristics of cost sensitivity differences across scenarios.The results indicate that EV users exhibit higher sensitivity to charging prices in scenarios such as towns,urban areas,and workplaces,typically opting to charge during off-peak hours with lower electricity prices.Conversely,in expressway and scenic spot scenarios,users prioritize charging efficiency over cost,showing lower cost sensitivity.These findings provide important theoretical and practical insights for implementing differentiated pricing strategies for charging facilities and enhancing user charging experiences.
作者
张利
高宇
经航
李乐欣
王瑞涵
ZHANG Li;GAO Yu;JING Hang;LI Lexin;WANG Ruihan(State Grid Smart Electric Vehicle Service Technology Co.,Ltd.,Beijing 100031,China;School of Management Science and Engineering,Beijing Information Science&Technology University,Beijing 102206,China)
出处
《湖北电力》
2025年第2期96-105,共10页
Hubei Electric Power
基金
国网智慧车联网技术有限公司自管项目(项目编号:523500250005)。
