Analysis Of Residential Electricity Consumption Behavior Based On Machine Learning

Under the historical background of intelligent information of power grid,with the allround development of electricity retail enterprises,power customer data mining work has also received attention and rapid growth.In order to meet the goal of intelligent use electricity of flexible and interactive,through mining power users' daily electricity consumption and analysis behavior of power consumption,improving the detection efficiency of abnormal electricity consumption,and identifying the law of user electricity consumption behavior,these provides a theoretical basis for power corporations to guide user scientifically use electricity.Therefore,this paper adopts intelligent algorithms based on machine learning to analyze the behavior of power consumers,detect the behaviors of abnormal electricity consumption and characteristics of power consumption,conduce to power corporations to strengthen management of electrical safety,and understand categories of power user.Reasonably formulate marketing strategies to meet demand of smart power utilization of residents.In this paper,a set of user analysis model is designed for resident behavior of electricity consumption.Firstly,in the data processing stage,the obtained data is analyzed,cleaned,aggregated,and relevant feature quantities are counted,and customers with abnormal data are screened out.Then in the machine learning model phase,the comprehensive performance of the single machine learning model and the ensemble learning model is compared,ensemble learning with superior comprehensive performance is selected to detect abnormal electricity consumption,and hierarchical management coefficients for suspected abnormal electricity consumption.Finally,in the user behavior analysis phase,the results of feature fusion are used to find the optimal number of clustering users by using the method of average group linkage,and then the users are clustered after determining the number of k-means clusters.According to specific analysis of the user clustering results,studied each behavior of type inhabitant users and provided some suggestions for the power corporations to formulate relevant strategies.The method proposed in this paper strengthens the power corporations scientifically to understanding for customers' electricity consumption,and is conducive to guid users orderly and intelligently in electricity utilization.This method provides a reference for power corporations to implement differentiated management and services for different users in terms of load forecasting,power grid planning,and power saling.