An improved bp neural network prediction method for transmission line radio interference

A BP neural network and radio interference technology, applied in forecasting, electrical digital data processing, special data processing applications, etc., can solve problems such as large prediction errors

Active Publication Date: 2018-05-01
STATE GRID CORP OF CHINA +1
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Problems solved by technology

Since the radio interference of transmission lines is also affected by environmental and geographic location factors, and the influence of these factors on the radio interference value shows a high degree of nonlinearity and uncertainty, it faces the constraints of applicable conditions and the prediction error is too large. The application in the actual circuit design will be limited to a certain extent

Method used

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  • An improved bp neural network prediction method for transmission line radio interference
  • An improved bp neural network prediction method for transmission line radio interference
  • An improved bp neural network prediction method for transmission line radio interference

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Embodiment 1

[0110] Such as Figure 1-2 As shown, the inventive method of this example is: obtain the factors that have influence on the radio interference Y of the transmission line as input data, including: voltage X 1 , current X 2 , wire diameter X 3 , wire section X 4 , split number X 5 , Splitting distance X 6 , soil resistivity X 7 , wire-to-ground distance X 8 , The distance between the wire and the measuring point X 9 , temperature X 10 , Humidity X 11 , air pressure X 12 , altitude X 13 ;

[0111] The input data contains 13 neurons, and the order of magnitude differs greatly. In order to ensure the equal status of each factor and speed up the convergence speed, the normalized preprocessing method is used to preprocess the input data and normalize the data to [-1 ,1] in the interval.

[0112] 1. Improved simulated annealing algorithm

[0113] Improved annealing process steps:

[0114] 1) given temperature t 0 , the initial state S is randomly generated, and the ini...

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Abstract

The invention relates to an improved BP neural network radio interference prediction method for power transmission lines. The method comprises the following steps: obtaining data parameters and preprocessing, establishing a BP neural network prediction model of data parameters, adopting genetic algorithm and simulated annealing algorithm to BP neural network The network is optimized and trained, and then the network is used to predict the radio interference of transmission lines. The invention has high prediction accuracy, good convergence and strong stability, avoids the problem of BP neural network falling into local minimum points, and has good guiding significance for the prediction of transmission line radio interference and the research of reducing radio interference.

Description

Technical field: [0001] The invention relates to a radio interference prediction method, more particularly to an improved BP neural network transmission line radio interference prediction method. Background technique: [0002] With the increase of the voltage level of the transmission line, the radio interference generated by the transmission line has aroused widespread concern. Reducing the electromagnetic environment impact of transmission lines and reducing the radio interference around the line is the work that designers in various countries have been studying, and how to accurately predict the radio interference of the line is the premise of the research work. At present, transmission line radio interference is predicted based on the empirical formula method and excitation function method recommended by CISPR. However, the mechanism of radio interference is very complicated, affected by many factors such as voltage, current, wire cross section, wire layout, meteorologi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/00G06Q50/06G06Q10/04G06N3/12
Inventor 马潇刘蕊莫娟段舒宁金欢方正刚刘铭
Owner STATE GRID CORP OF CHINA
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