Identification method and system for key factors affecting transmission line galloping
A transmission line and key factor technology, applied in the identification method and system field of key factors affecting transmission line galloping, can solve problems such as loose fittings and bolts, broken wires, power outages in the power grid, etc., achieve high practical value, improve accuracy, and facilitate operation Effect
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Embodiment 1
[0023] This embodiment discloses a method for identifying key factors affecting transmission line galloping, which includes the following steps,
[0024] (1) Obtain the galloping data of the transmission line of a provincial power grid and the corresponding factors such as terrain, line direction, wind speed, wind direction, temperature, air pressure, humidity, precipitation, unevenness of ice coating, and ice thickness.
[0025] (2), respectively calculate the topographic factor F e , Line direction factor F d , wind speed factor F ws , wind direction factor F wd , temperature factor F t , air pressure factor F p , humidity factor F m , Precipitation factor F r , Icing non-uniformity factor F n , ice thickness factor F c The correlation coefficient between etc. and transmission line galloping is R e =0.21,R d =0.52,R ws =0.25,R wd =0.42,R t =0.13,R p =0.02,R m =0.03, R r =0.12,R n =0.66,R c =-0.38.
[0026] (3), set a correlation coefficient threshold T = 0...
Embodiment 2
[0035] On the basis of the above-mentioned embodiment 1, those skilled in the art should understand that: the method for identifying key factors affecting transmission line gallop disclosed in the present invention can be condensed into the following steps, as follows: figure 1 shown, including:
[0036] Step S1. Acquiring transmission line galloping data and corresponding at least two potential key factors.
[0037] Step S2, establish the linear regression equation between each potential key factor and the galloping of the transmission line, calculate the error of each linear regression equation, and determine the linear regression equation with the smallest error as the benchmark regression equation, and the potential key factor corresponding to the benchmark regression equation The factor is the first potential key factor.
[0038]Step S3, select the second potential key factor from the remaining potential key factors to adjust the benchmark regression equation, and when t...
Embodiment 3
[0040] Corresponding to the above method, this embodiment provides a system for identifying key factors affecting transmission line galloping, including:
[0041] The first module is used to obtain galloping data of transmission lines and corresponding at least two potential key factors;
[0042] The second module is used to establish the linear regression equation between each potential key factor and the galloping of the transmission line, calculate the error of each linear regression equation, and determine the linear regression equation with the smallest error as the benchmark regression equation, which corresponds to The potential key factor of is the first potential key factor;
[0043] The third module is used to select the second potential key factor from the remaining potential key factors to adjust the benchmark regression equation. When the error of the adjusted benchmark regression equation is less than or equal to the error of the benchmark regression equation bef...
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