基于朴素贝叶斯的电网用户行为分析

针对电网数据利用率低、精度低、分析结果粗糙和分析层面浅等问题,提出了一种基于朴素贝叶斯分析的电网用户行为分析方法.使用模糊C均值聚类将电网用户的用电数据聚类为不同的用电模式,使用朴素贝叶斯分类器将用户的用电行为分为不同的类别,提取出其中主要的用电模式.某纺织企业的48点负荷数据仿真与测试结果表明,所提出方法在分析用户用电模式时的有效性良好,为电力系统的调控与运行提供了一种合理、有效的方法.

Analysis of electrical grid user behavior based on Naive Bayesian

Aiming at the problems of low utilization rate of power grid, low precision, rough analysis results and shallow analysis level, a behavior analysis method of electrical grid users based on Naive Bayesian analysis was proposed. A fuzzy C-means clustering method was used to cluster the electricity consumption data of electrical grid users into different power consumption modes, a Naive Bayes classifier was used to classify the electricity consumption behavior of users into different categories, and the main electricity consumption modes were extracted. The simulation and test results of 48-point load data from a textile enterprise show that the as-proposed method is effective in analyzing the electricity consumption modes of users and provides a reasonable and effective method for the regulation and operation of power system.