Abnormal power consumption detection method based on neural network

A technology of abnormal electricity consumption and neural network, applied in neural learning methods, biological neural network models, etc., can solve the problems of consuming human and material resources, unfavorable power industry management, low efficiency, etc., saving human and material resources and narrowing the scope of investigation. , the effect of reducing costs

Inactive Publication Date: 2017-05-31
STATE GRID CORP OF CHINA +2
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Problems solved by technology

This processing method consumes a lot of manpower and material resources, and has low efficiency and poor effect. At the same time, this method has great human factors, which is not conducive to the management of the electric power industry.

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  • Abnormal power consumption detection method based on neural network
  • Abnormal power consumption detection method based on neural network
  • Abnormal power consumption detection method based on neural network

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Embodiment

[0074] Embodiment: With the development of artificial intelligence, the application of artificial neural network in classification and prediction is being widely accepted and studied by people. The principle of artificial neural network algorithm is to let the computer sum up how to identify these abnormal classifications, and The classified data set is used as training data, and the algorithm is allowed to find the structural knowledge in it. Not only the classification result is better, but also the efficiency of the algorithm is very high.

[0075] Introduction to neural network: Neural network algorithm is one of the most important algorithms in machine learning. It simulates the neural network of the human brain. Through learning induction, an algorithm model that can be used for classification and prediction is obtained; the working principle of neural network is similar to that of human neurons. How it works, a simple neural network can be divided into an input layer, a ...

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Abstract

The invention relates to an abnormal power consumption detection method based on a neural network. The method diagnoses and analyzes an operation condition of equipment based on an established abnormal power consumption detection model, judges whether metering equipment is in a normal operation condition and realizes an aid decision-making function. The method concretely comprises the following steps of (1) data acquisition: data are mainly from electric energy metering data, operation condition data and event recording data in an electric energy meter and an acquisition terminal; (2) data cleaning: the used data can enter the model after being subjected to data cleaning and screening; (3) data classification: after data cleaning completes, the data are calibrated, one column of numbers for representing data classification is added at the end of the data for classification, and the data subjected to data calibration are integrated into training data; (4) a modeling process: an algorithm model is constructed in a manner of supervised learning; (5) model implementation; and (6) result analysis: the final accuracy rate of abnormal power consumption found by the model maintains at a high level.

Description

technical field [0001] The invention relates to a method for detecting abnormal power consumption based on a neural network, and belongs to the technical field of detecting abnormal power consumption of power grids. Background technique [0002] With the continuous improvement of informatization, the era of big data has arrived, and mining valuable information from a large amount of data with low value density has become a hot issue that all walks of life pay close attention to. For the power industry, with the continuous improvement of the informatization level of the power system and the rapid growth of the data volume of distribution and consumption, various devices and systems have a large amount of data to be processed, the data scale is huge, and the event information contained is various. But so far, it still faces the important problem of "massive data and lack of information". [0003] At the same time, due to a variety of communication failures, equipment failures...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08
CPCG06N3/084
Inventor 汪泽州沈春林刘群顾卫华黄建伟朱胜洪朱升涛吴亚洲刘章银方李明胡松松舒能文邓亮赵海波
Owner STATE GRID CORP OF CHINA
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