Electric transmission line icing grade long-term prediction method based on support vector classification

A technology of support vector classification and transmission lines, which is applied in the field of long-term forecasting, can solve the problems that the research on the forecasting method of grid icing level has not yet been reported, and achieve the effect of good training and learning performance, convenient operation and clear thinking

Active Publication Date: 2015-07-08
STATE GRID CORP OF CHINA +2
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Problems solved by technology

At present, the research on the prediction method of power grid icin

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  • Electric transmission line icing grade long-term prediction method based on support vector classification
  • Electric transmission line icing grade long-term prediction method based on support vector classification
  • Electric transmission line icing grade long-term prediction method based on support vector classification

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Embodiment Construction

[0020] The present invention will be described in further detail below in conjunction with specific examples.

[0021] A long-term prediction method of transmission line icing level based on support vector classification, comprising the following steps:

[0022] (1) Grid icing grade division

[0023] According to the historical statistical data of the annual average number of ice-covered days of the power grid and the anti-icing ability of the existing ice-melting measures, the power grid icing is divided into several levels. Taking the power grid in Hunan Province as an example, the annual average icing days of the power grid are within 3 days for mild icing, 3 to 5 days (including 3 days) for moderate icing, and 5 to 11 days (including 5 days) for severe icing. Ice, 11 days and above is the ice of special severity, in which light ice is defined as level 1, moderate ice is defined as level 2, severe ice is defined as level 3, and particularly severe ice is defined as level 4...

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Abstract

The invention discloses an electric transmission line icing grade long-term prediction method based on support vector classification. The electric transmission line icing grade long-term prediction method comprises the steps of grading power grid icing, extracting icing grade predictive factors, conducting data normalization on the power grid icing grade predictive factors, establishing a classification model based on multi-classification support vectors and conducting long-term prediction on the power grid icing grade. By the adoption of the prediction method, the power grid icing grade long-term prediction precision can be effectively improved, reliable data support is provided for power grid ice resistance, the prediction method has important significance in taking power grid ice resistance measures in advance and guaranteeing the reliability of operation of a power grid, the concept is clear, operation is convenient, the practicability is high, the nonlinear mapping relationship between the power grid icing predictive factors and the power grid icing grade can be effectively processed, and a good training and learning performance is achieved for small sample data.

Description

technical field [0001] The invention relates to the technical field of electrical engineering, in particular to a long-term prediction method for transmission line icing level based on support vector classification. Background technique [0002] Affected by the strong cold air in winter, the power grid in southern my country is vulnerable to icing disasters, resulting in large-scale collapsed towers and disconnection accidents, which seriously threatens the safe and stable operation of the power grid, especially as the construction and operation of my country's UHV power grid gradually extends to icing disasters In severe areas, the prevention and control of power grid icing disasters is particularly urgent. The long-term prediction of grid icing level can provide a longer forecast period for grid anti-icing, gain valuable time for the deployment of corresponding anti-icing measures for different icing levels in advance, and can significantly improve the efficiency and effect...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06K9/62
Inventor 陆佳政郭俊张红先方针李波谭艳军
Owner STATE GRID CORP OF CHINA
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