| 赵阳,胡诗尧,杨书强,冯 成,王 毅.售电市场环境下基于数据驱动的用户用电行为分析[J].电力需求侧管理,2020,22(4):45-50 |
| 售电市场环境下基于数据驱动的用户用电行为分析 |
| Analysis of data⁃driven based users’electricity consumption behavior in retail market |
| 投稿时间：2020-05-06 修订日期：2020-05-26 |
| DOI：DOI:10. 3969 / j. issn. 1009-1831. 2020. 04. 010 |
| 中文关键词: 售电市场 智能电能表 用户行为 聚类分析 |
| 英文关键词: retail market smart meter consumer behavior clustering analysis |
| 基金项目:国家自然科学基金项目（71961137004, U1766212）；清华大学自主科研计划资助（20193080026） |
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| 中文摘要: |
| 智能电能表能够实时采集用户的用电数据，在未来数字化配用电系统中将得到广泛普及。在我国售电市场进一步放开并逐步繁荣的背景下，售电商能够通过分析海量用户用电数据，掌握用户用电行为，从而实现更好的服务。探讨了面向售电市场用户行为分析的特征提取方法，采用了 k-means、模糊聚类、层次聚类等不同的聚类算法实现典型用户用电行为的模式提取，分析了不同用户用电行为的基本特征。对爱尔兰地区6 445名用户的公开用电数据进行实证分析，结果表明，该方法能够有效提取用户的用电行为模式，分辨用户用电行为异同。 |
| 英文摘要: |
| Smart meters can collect power consumption data of consumers in real time, and will be widely popularized in the future digital power distribution system. In the context of the further liberalization of domestic electricity sales market and its gradual prosperity, electricity retailers can analyze the mass electricity consumption data of the consumers to grasp the electricity consumption behavior, thereby achieving better services. The feature extraction method for user behavior analysis of electricity sales market is discussed. K- means, fuzzy clustering, hierarchical clustering and other clustering algorithms are adopted to achieve the pattern extraction of typical user electricity behavior, and the basic features of electricity consumption behavior of different users are analyzed.An empirical analysis is conducted on the public electricity data of 6 445 consumers in Ireland. The result proves that the proposed method can effectively extract the patterns of behaviors, and distinguish the differences and similarities among users. |
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