GRNN applied to study the Lightning Shielding Performance for EHV&UHV Transmission Line

Lightning shielding failure is the main factor to threat the safety and reliability of EHV transmission lines. In this paper, the small-scale model experiments of lightning shielding performance of EHV transmission lines were made, taking the various influencing factors into account, including protection angle alpha , the gradient of the hillside thetas, the height of the gully H , the conductor potential U , non-vertical leader angle beta and the position of lightning stroke point (X,y) , showing the lightning stroke probability P_a has the hidden non-linear function relation with the factors above. Due to the fact that the generalized regression neural network (GRNN) has several advantages over the back-propagation network (BP) such as very short training time and guaranteed performance even with sparse data, it is applied to simulate the complex non-linear function relationship between the lightning stroke probability Pa and these various influencing factors. A lot of simulation was carried out in Matlab and the feasibility and accuracy of the proposed GRNN are verified.