Pollution flashover index forecasting method for regional power grid

A technology of regional power grid and prediction method, which is applied in neural learning method, testing dielectric strength, biological neural network model, etc., can solve the problem of inability to comprehensively monitor and predict the power grid in real time, single modeling object, and the distribution of monitoring points of leakage current. Limited scope, etc.
CN101893674AActive Publication Date: 2010-11-24STATE GRID CORP OF CHINA +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
STATE GRID CORP OF CHINA
Publication Date
2010-11-24

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Abstract

The invention relates to a pollution flashover index forecasting method for a regional power grid, belonging to the technical field of transmission and distribution monitoring. The method of the invention comprises the following steps: (1) forecasting the current value of the equivalent salt deposit density in real time by an insulator surface equivalent salt deposit density forecasting model; (2) forecasting pollution flashover critical voltage by an insulator pollution flashover critical voltage forecasting model; (3) forecasting the insulator pollution flashover index of the power grid by a pollution flashover graded forecasting and prewarning model; and (4) judging the state. The invention has the advantages of providing a multivariable equivalent salt deposit density time sequence forecasting model based on phase space reconstruction, solving by a supporting vector machine model, solving the forecasting problem under the conditions of small sample of equivalent salt deposit density data and noise, and improving the forecasting prediction.
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Description

technical field

[0001] The invention belongs to the technical field of power transmission and distribution monitoring, and in particular relates to a method for predicting pollution flashover index of a regional power grid. Background technique

[0002] During the operation of the power grid, the pollution flashover on the surface of the insulator has a very adverse effect on the power supply system. At present, there are many prediction methods for the pollution flashover on the insulator surface, mainly focusing on the prediction of the equivalent salt density on the surface of the insulator, the insulator Prediction of pollution flashover voltage and pollution flashover prediction based on leakage current.

[0003] Among them, the neural network prediction of equivalent salt density and the support vector machine prediction of pollution flashover voltage all use nonlinear modeling methods to simulate the multidimensional nonlinear relationship between these two parameters...

Claims

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