User electricity stealing detection method and system based on DLSTM-RF

Abstract

The invention discloses a user electricity stealing detection method and system based on DLSTM-RF, and the method comprises the steps: constructing a related data set which is used as the input data of a DLSTM-RF model, training the DLSTM-RF model, and generating a user electricity stealing prediction model; a DLSTM-RF model is constructed, and the DLSTM-RF model is used for generating a user electricity stealing prediction model through the related data set; the DLSTM-RF model is trained through a related data set, a user electricity stealing prediction model is generated, and the user electricity stealing prediction model is used for analyzing and learning information in a power grid system, finding out electricity stealing users and reducing unnecessary power production by managing the electricity stealing users; according to the invention, the electricity stealing information of the user is detected and converted with the carbon emission information, so that the spanning from the electricity utilization information to the carbon reduction information is realized, and a certain reference is provided for realizing the carbon control of the user side of the power grid.

Description

technical field [0001] The present application relates to the technical field of electricity theft monitoring, in particular, to a DLSTM-RF-based user electricity theft detection method and system. Background technique [0002] With the rapid development of social economy, the global carbon emission problem is becoming increasingly serious. In recent years, low-carbon structural changes are urgently required, and we are now facing the challenge of a large amount of emission reduction and a tight time frame. Carbon dioxide emissions from energy combustion are 9.7 billion tons, accounting for 88%, and the power industry is about 3.9 billion tons, accounting for about 35%. The carbon level of the power industry directly affects the implementation of international commitments on carbon emission reduction. [0003] The issue of carbon emissions is a global problem that restricts social development. my country's low-carbon structural reforms are urgently required, and the carbon...

AI Technical Summary

Problems solved by technology

At present, there is a deep learning-based user abnormal power consumption pattern detection model, and a feature extraction network and a multi-layer feature matching network are constructed, which have high accuracy. There is no relevant report on the leap technology from electricity consumption information to carbon reduction information. Therefore, there is an urgent need for a technical solution that can associate electricity theft information with carbon emission information to solve existing technical problems

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