Power transmission line mountain fire clustering quantitative forecasting method and system

Abstract

The invention discloses a power transmission line mountain fire clustering quantitative forecasting method. In steps 1-3, the multi-time coordinate mountain fire forecasting time axis is obtained by means of a cluster analysis method, and the optimal forecasting scale of the forecasting area is obtained by the spatial scale contrast analysis method; and on this basis, in steps 4-5, a forecasting model is established according to the space-time distribution rule obtained in the steps 1-3, and the daily mountain fire amount in the area is forecasted. The invention further discloses a power transmission line mountain fire clustering quantitative forecasting system. By calculating the node historical mountain fire points of each space unit, the air humidity suppressing coefficient and the combustible matter damping coefficient of the day to be measured, the mountain fire forecasting rainfall index of the day to be measured, and the continuous drought influence factor of the day to be measured, the mountain fire generation expect number of the day to be measured of each space unit is predicted, the operationality is high, the forecasting accuracy is high, and the power transmission line mountain fire quantitative forecasting refinement degree is improved.

Description

technical field [0001] The invention relates to the technical field of power transmission and distribution, in particular to a method and system for clustering and quantitative forecasting of mountain fires on power transmission lines. Background technique [0002] Affected by people's customs of using fire in production and life, large-scale wildfires are extremely prone to occur in transmission line corridors, causing multiple lines to trip and blackout at the same time, and even cause the grid to collapse. Therefore, wildfire has become a hot issue that seriously threatens the safe operation of large power grids and the normal power supply of society. The disposal of mountain fires on transmission lines has high requirements on timeliness, and trips are usually caused 1 to 1.5 hours after the occurrence of wildfires. Shortening the rescue distance of wildfires can improve the rescue rate of wildfires. Carrying out mountain fire forecasting on power transmission lines can...

AI Technical Summary

Problems solved by technology

The invention patent with the patent number 20121002726.3 proposes a method for predicting mountain fires on transmission lines, which can predict the occurrence of mountain fires, that is, whether mountain fires occur, but cannot give the density of mountain fires, and cannot judge the occurrence of mountain fires near transmission lines the severity of

The invention patent with the patent number of 201510255860.4 proposes a transmission line density prediction method. First, its historical data rely on the unified assignment of artificially defined wildfire high-incidence periods, and fail to divide the time coordinates according to the clustering conclusion of the wildfire time series. It is uniformly applicable to areas with different patterns of man-made fire use, and cannot effectively overcome the randomness of wildfire occurrence time; secondly, there are spatial differences in vegetation types, fire use customs and other factors in various places, and the prediction scale greatly affects the accuracy of transmission line wildfire forecasting. Accuracy, the current method has not yet involved the selection of the spatial scale of wildfire forecasting; finally, this method does not consider the suppression effect of high air humidity on the occurrence of wildfires, the forecast accuracy needs to be further improved, and it is difficult to accurately guide the deployment of wildfire prevention equipment

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