Research On User Stealing Identification Based On Big Data Analysis Of Power Information

In the construction of national smart grid,anti-stealing electricity is an indispensable infrastructure link.With the development of anti-theft technology and methods towards science and technology and information,its concealment has been greatly improved,resulting in more and more challenges to many previous anti-theft means and methods.With the continuous upgrading of metering equipment and the rapid development of computer network technology,it is the latest technical means of anti-stealing electricity in the new era to use the cloud storage capacity of massive data of computer network and the big data analysis platform to establish an analysis method of suspected stealing electricity based on data mining technology.In the data analysis,based on the company database of Hebei Province,relevant index data such as user electricity consumption information and electricity marketing information are collected for analysis.This paper studies the algorithm of big data analysis,uses logistic regression model and Gaussian distribution as the big data analysis algorithm,and applies the big data analysis method to anti-theft work.From data collection,data cleaning,data conversion,feature extraction,model construction and result evaluation,the anti-theft model was successfully constructed,and finally the positioning of suspected users and the prediction of the probability index of suspected electricity theft were realized.Through data visualization technology,the results of anti-stealing electricity are vividly and intuitively displayed,which is more conducive to users’ observation and analysis.Based on the massive data of the electricity consumption information collection system,starting from the characteristics of collecting electricity data and basic information of users,an anti-stealing analysis model is established,and various abnormal operation data generated in the practice of investigating and handling electricity theft are collected and analyzed,so that automatic early warning and warning can be realized,the efficiency and accuracy of investigating and handling electricity theft are greatly improved,and the occurrence of electricity stealing behavior of users can be restrained,thus ensuring the security of power grid and improving the company’s benefits.In this paper,by using big data technology,the anti-stealing model is used to intelligently analyze and judge the suspected users,and the results of the model are displayed in various directions,and some valuable achievements have been achieved,which has played a certain role in promoting the discovery of users and the containment of stealing behavior.