Modeling PD inception voltage of epoxy resin post insulators using an adaptive neural network

One of the parameters used to characterize the partial discharge (PD) behavior is its inception voltage. The partial discharge inception voltage (PDIV) should always be higher than the operating voltage to ensure that PD does not occur at or near operating voltage. Under these circumstances, other PD parameters such as apparent charge, energy dissipation need not be considered. This paper deals with modeling of PDIV of epoxy-resin post insulators using a neural network (NN). The PDIV is obtained experimentally for various shapes and sizes of post insulators, with a working voltage in the range of 3.3 to 33 kV. The electrode spacing d and creepage length l are the key parameters employed for the present modeling. An adaptively trained multilayer NN is employed for the modeling. Detailed studies are carried out to optimize the NN parameters for minimum error. The model results obtained closely follow the experimental data indicating the effectiveness of NN as an efficient tool in estimation of PDIV of epoxy-resin post insulators.