基于多源多维度用能数据的用户标签萃取方法研究

Research on User Label Extraction Method Based on Multi-source and Multi-dimensional Energy Consumption Data

随着电力行业数字化、智能化水平稳步提升,电力公司利用大数据技术精准识别用户需求、掌握用户用能规律,进而满足用户多样化的用能需求成为营造良好用电体验的关键。为此提出一种基于多源多维度用能数据的用户标签萃取方法,旨在通过采用模糊C均值聚类算法进行标签聚类、用户智能画像,更好支撑用户用电行为掌握、精准营销策略执行,辅助制定电力需求侧响应策略,推动电力服务质效提升。

With the steady improvement of the digital and intelligent level of the power industry, power companies use big data technology to accurately identify user needs, master the rules of user energy consumption, and then meet the diversified energy demand of users, which is the key to create a good electricity experience. In this paper, a user label extraction method based on multi-source and multi-dimensional energy consumption data is proposed, aiming at using fuzzy C-means clustering algorithm for label clustering and user intelligent portrait to better support users′ power consumption behavior and accurate marketing strategy implementation, assist in the formulation of power demand side response strategy, and promote the improvement of power service quality.