Probability prediction of transmission line breakage and tower topple over under wind disaster considering the joint distribution of wind speed and wind direction
DOI：10.7667/PSPC180109
Key Words:windstorm  joint distribution of wind speed and wind direction  probabilistic analysis  line damage and tower collapse  numerical weather prediction
Author NameAffiliation
ZHU Ling Huizhou Power Supply Bureau of Guangdong Power Grid Corporation, Huizhou 516001, China 
CHEN Taowei Huizhou Power Supply Bureau of Guangdong Power Grid Corporation, Huizhou 516001, China 
ZHOU Chen School of Electric Power, South China University of Technology, Guangzhou 510640, China 
DENG Honglei School of Electric Power, South China University of Technology, Guangzhou 510640, China 
XIA Qiao School of Electric Power, South China University of Technology, Guangzhou 510640, China 
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Abstract:In view of the deficiencies that it is difficult to obtain the data of the wind speed and direction of the actual line and the prediction error of transmission line breakage and tower topple over is higher than that of the existing wind disaster, a probability prediction model of transmission line breakage and tower topple over with the correlation of wind speed and wind direction is proposed. The model uses the product of wind speed probability density function and wind direction frequency to express the joint probability density function and calculate the effective optimal probability distribution types and parameters of each wind direction of transmission line height. The wind load model of transmission lines and the wind load model of the tower are used to calculate the maximum wind speed that the lines and the towers can bear under each direction. Through processing numerical weather forecast data and taking the altitude correction and interpolation mapping after forecasting wind speed data as input parameters, it achieves the probability prediction of transmission line breakage and tower topple over when the line meteorological data is insufficient. This work is supported by Science and Technology Project of China Southern Power Grid Company (No. 031300KK52160012).
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