Analyzing the impact of radio interference(RI)variation during foul weather conditions is an area that has received limited study.This paper provides a statistical analysis of RI measurements obtained from a long-term...Analyzing the impact of radio interference(RI)variation during foul weather conditions is an area that has received limited study.This paper provides a statistical analysis of RI measurements obtained from a long-term observation station close to the world’s first commercially operating 1000 kV UHV AC double-circuit transmission line in China.During six months of observations,the impact of RI was studied on the line during fog,drizzle,and light snow and rain.It was found that RI increases linearly with the natural logarithm of the precipitation intensity.The Levenberg-Marquardt algorithm(LMA)is employed to fit the RI value with the precipitation intensity.The reasonable distribution of RI in different foul weather is verified by one-sample K-S test.This test is seen as beneficial for further RI prediction based on statistical weather mode.展开更多
基金supported in part by the National Basic Research Program(973 Program)under Grant 2011CB209402-3the Science and Technology Project of the State Grid Corporation of China under Grant GY71-15-033.
文摘Analyzing the impact of radio interference(RI)variation during foul weather conditions is an area that has received limited study.This paper provides a statistical analysis of RI measurements obtained from a long-term observation station close to the world’s first commercially operating 1000 kV UHV AC double-circuit transmission line in China.During six months of observations,the impact of RI was studied on the line during fog,drizzle,and light snow and rain.It was found that RI increases linearly with the natural logarithm of the precipitation intensity.The Levenberg-Marquardt algorithm(LMA)is employed to fit the RI value with the precipitation intensity.The reasonable distribution of RI in different foul weather is verified by one-sample K-S test.This test is seen as beneficial for further RI prediction based on statistical weather mode.
