基于数据驱动方法的疫情阶段电力用户负荷特性画像模型

电力用户负荷画像建模是一种面向用户的、通过挖掘用电数据中的负荷特性建立差异化画像标签的重要方法,现有研究方法多侧重于画像方法的研究,而缺乏完善的负荷特性标签体系.文章提出了一种基于数据驱动的负荷特性分析通用方法,从调度部门最关注的用电规律性、平顺度、负荷调控能力以及疫情影响度四方面构建负荷特性标签体系.首先,采用模糊C...

Load Characteristic Portrait Model of Power Users in Epidemic Stage Applying Data-Driven Method

Load portrait modeling of power user is an important user-oriented method to create differentiated labels by mining the load characteristics in power consumption data. Most of the existing research focuses on the study of portrait methods, but lacks comprehensive load characteristic label system. This paper proposes a general method of load characteristic analysis based on data-driven. The load characteristic label system is constructed from power consumption regularity, smoothness, load control capability and epidemic impact, which are most concerned by dispatching department. Firstly, the typical load curve is extracted from massive actual load data by using fuzzy C-means clustering algorithm. Considering the power consumption characteristics of each industry from above four aspects, a comprehensive load characteristic label system and the load characteristic portrait models of different power users are established. Secondly, the load characteristic label is refined and every definition and calculation method of corresponding index is given. Furthermore, the index boundary is determined by fuzzy clustering algorithm, and the smoothness label is scored by entropy weight method. Finally, the data of typical users in different industries are analyzed from an example, and universal index boundaries are given, which provide a new idea for load modeling of users in various industries.