基于用户日负荷曲线的用电行业分类与综合方法

A Classifying and Synthesizing Method of Power Consumer Industry Based on the Daily Load Profile

利用实时日负荷曲线进行综合负荷在线建模需解决用户日负荷曲线的正确分类与有效综合以及变电站日负荷曲线的行业构成比例识别2个关键问题。运用模糊C均值聚类和模式识别原理,提出一种基于日负荷曲线的用户所属用电行业的分类与综合方法。首先在有功功率空间进行用户的行业归属分类和行业用户精选,得到行业综合日负荷曲线;然后在定义的特征空间获得描述行业综合用电特性的特征参数,并以此作为检验分类与综合结果合理性的测度指标。实际应用表明,该方法物理概念清晰、简便、实用。

The aggregate load online modeling with daily load profile has two key points to be solved,one is the appropriate classification and effective synthesis of customers＇ daily load profiles,the other is the industry composition ratio of the daily load profile in substations. Applying the theory of fuzzy C means clustering and pattern recognition,the authors propose a new method for consumer industry classification and synthesis with daily load profile of the power consumer. First,the customers are classified and selected on the basis of the active power in order to obtain the synthetical daily load curve of the industry. Then,the eigen-value parameters are obtained,by which the synthetical characteristics of the industry can be described and the results of classification and synthesis can be tested. Actual application shows that the method is clear in concept,convenient and practical.