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Electricity stealing identification method based on a support vector machine

A technology of support vector machine and identification method, applied in the direction of instruments, data processing applications, resources, etc., can solve the problems of low efficiency, low accuracy, poor timeliness, etc., to reduce adverse effects, ensure normal operation, and improve electricity stealing Investigating the effect of efficiency

Active Publication Date: 2019-04-05
SATE GRID ZHEJIANG CHANGXING COUNTY POWER SUPPLY +4
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Problems solved by technology

The current anti-stealing technology only relies on the monthly power changes of users and the abnormal line loss in the station area to determine the suspected users of electricity theft, which has poor timeliness and low accuracy, and the efficiency of on-site investigations to find electricity theft is not high.

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  • Electricity stealing identification method based on a support vector machine
  • Electricity stealing identification method based on a support vector machine
  • Electricity stealing identification method based on a support vector machine

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Embodiment Construction

[0049] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0050] The present invention comprises the following steps:

[0051] 1) Obtain electricity consumption data of electricity users;

[0052] 2) Data preprocessing: using the normalization method of linear function, namely Among them, x(k) represents any sample value, min(x(n)) represents the minimum value of the sample, and max(x(n)) represents the maximum value of the sample; convert y(k) to be between 0 and 1 The number between to eliminate the influence of the sample by dimension and attribute;

[0053] 2) Volatility calculation;

[0054] Define the ratio of the standard deviation to the mean value as the power fluctuation coefficient, that is In the formula, d i is the user's daily power, is the average value of daily electricity, N is the cumulative number of days, σ is the standard deviation, and μ is the mean value;...

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Abstract

The invention discloses an electricity larceny identification method based on a support vector machine, and relates to an electricity larceny identification method. The current electricity larceny prevention technology only depends on monthly electric quantity change of a user and line loss abnormity of a transformer area to determine suspected electricity larceny households, and has the problemsof poor timeliness, low accuracy, and low efficiency when electricity larceny behaviors are found through on-site investigation. The method comprises the steps of fluctuation ratio calculation, normalload data sample selection, establishment of an SVM normal load data classification model according to the normal load data samples, electricity stealing identification according to the SVM normal load data classification model, separation of suspected outliers of electricity stealing, determination of electricity stealing sample points and setting of electricity stealing point alarms. Accordingto the technical scheme, the novel electricity stealing identification method is combined with a method for calculating the electric quantity fluctuation rate and a support vector machine analysis method. Appropriate sample data are selected for the support vector machine by calculating the electric quantity fluctuation rate, so that adverse effects of sample problems on a detection analysis result can be effectively reduced, and an electricity stealing detection result is more accurate.

Description

technical field [0001] The invention relates to a method for identifying electricity theft, in particular to an identification method for electricity theft based on a support vector machine. Background technique [0002] With the emergence of high-tech means of stealing electricity, the problem of stealing electricity has become more and more prominent. The annual economic losses caused by electricity theft in the country are about tens of billions of yuan, which has seriously endangered the normal operation of the economic order. The current anti-stealing technology only relies on the monthly power changes of users and the abnormal line loss in the station area to determine the suspected electricity theft, which has the problems of poor timeliness, low accuracy, and low efficiency in on-site investigations to find electricity theft. Contents of the invention [0003] The technical problem to be solved and the technical task proposed by the present invention are to perfect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/0639G06Q50/06Y02D10/00
Inventor 卢峰尹小明裘华东丁学峰谢岳叶方彬郑松松赵立美王伟峰
Owner SATE GRID ZHEJIANG CHANGXING COUNTY POWER SUPPLY
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