基于聚类的用户用电行为分析研究

Research on User’s Power Behavior Based on Clustering

伴随着我国经济的发展,作为经济发展的保障电力能源消耗量也在不断增加。用电数据快速提高,这就需要针对这些数据进行采集和分析,运用数据挖掘技术了解用户用电的行为特征,为用户用电提供更好的服务与保障。本文主要是以聚类分析方法研究用户的用电行为。通过针对不同场景的用户用电分类调度,合理优化了用户智能需求效应结果,并且计算难度得到降低,为我国电力企业根据用户用电规律进行合理供电提供借鉴。

Along with the development of China’s economy, the consumption of electricity and energy as a guarantee for economic development is also increasing. The rapid improvement of electricity consumption data requires collection and analysis of these data, and the use of data mining technology to understand the behavior characteristics of users’ electricity consumption, and provide better service and guarantee for national electricity consumption. This paper mainly studies the user’s electricity usage behavior by cluster analysis. Through the user classification and scheduling for different scenarios, the user intelligent demand effect result is reasonably optimized, and the calculation difficulty is reduced, which provides reference for China to make reasonable power supply according to the user’s electricity consumption law.