Power consumer electricity stealing behavior analysis method based on big data and machine learning

A machine learning and power user technology, applied in data processing applications, instruments, computer components, etc., can solve problems such as external signal interference and power theft

Pending Publication Date: 2019-05-14
韩霞 +5
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  • Abstract
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Problems solved by technology

[0004] Ø External signal interference stealing electricity;

Method used

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  • Power consumer electricity stealing behavior analysis method based on big data and machine learning
  • Power consumer electricity stealing behavior analysis method based on big data and machine learning

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Embodiment Construction

[0039] The present invention will be further described below in conjunction with examples with reference to the accompanying drawings.

[0040] refer to figure 1 As shown, a method for analyzing power user stealing behavior based on big data and machine learning, the method includes the following steps:

[0041] Step 1. Extract a large number of user electricity consumption data and use a clustering algorithm to establish a graph of electricity consumption behavior patterns;

[0042] Step 2. Analyze the clustering results, and combine business experience and actual data to obtain the normal power consumption behavior pattern and the behavior pattern of the electricity stealing user;

[0043]Step 3. Based on the behavior patterns of electricity stealing users, extract the characteristics of electricity consumption behavior of users in such patterns, and establish an algorithm analysis model;

[0044] Step 4. Use the test data set and the training data set to train and evaluat...

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Abstract

The invention discloses a power consumer electricity stealing behavior analysis method based on big data and machine learning. The method comprises the following steps: 1, extracting a large amount ofuser electricity consumption data, and establishing an electricity consumption behavior pattern map by using a clustering algorithm; 2, analyzing a clustering result, and obtaining a normal electricity utilization behavior mode and a behavior mode to which an electricity stealing user belongs in combination with business experience and actual data; 3, on the basis of the behavior pattern to whichthe electricity larceny user belongs, extracting electricity consumption behavior characteristics of the user in the mode, and establishing an algorithm analysis model; 4, training and evaluating themodel by using the test data set and the training data set to obtain an optimal model; 5, monitoring the abnormal action of the user by combining line loss, metering abnormity and the like of the transformer area; and 6, tracking and monitoring the highly suspected electricity stealing user or generating an on-site patrol work order and a processing system. The invention discloses a correspondinganalysis processing system.

Description

technical field [0001] The invention relates to a power user stealing behavior analysis method and processing system based on big data and machine learning. Background technique [0002] In recent years, with the increasing development of the market economy, electric energy as a clean energy has been widely used in various fields of the national economy and in the production and life of the people. In order to seek huge profits, private owners ignore national laws and regulations and steal national electric energy by any means. Rampant electricity theft has seriously damaged the legitimate rights and interests of enterprises and individuals, disrupted the normal order of power supply and consumption, hindered the development of electric power industry, and brought serious threats to the safe use of electricity. Stealing electricity has become a social problem that cannot be ignored. The categories of power theft are currently mainly divided into the following three categor...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q50/06
Inventor 韩霞谢振刚郭易鑫罗义钊程树英蒋海峰贺鹏远王佳盛
Owner 韩霞
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