Electro-thermal modeling of surge arrester based on adaptive power loss estimation using finite element method.

This paper proposes an adaptive model for electro-thermal analysis of metal oxide surge arresters based on finite element method. The input of the proposed model has been derived from power loss curve using adaptive network based fuzzy inference system (ANFIS). Moreover, degradation factor has been introduced as a new index to represent operating history of metal oxide surge arrester. Therefore, applied voltage, temperature, and degradation factor have been considered as inputs in the ANFIS model to obtain accurate power loss which is of paramount importance in electro-thermal analysis. High voltage experimental setup and an oven have been prepared to acquire data for the proposed model. Degrading effect has been undertaken by measurement of the voltage-current characteristic of used and degraded varistors. The effect of assembling process, in addition, has been considered using different virgin (not degraded) varistors in experimental measurements. In addition, according to the IEC standard, the aging effect has been obtained experimentally by putting the varistor under 115 °C and continuous operating voltage for 1000 h. To validate the results of the electro-thermal model, thermal infrared camera has been used under different applied voltages. Obtained results show that the electro-thermal behavior of surge arrester is predictable with high precision through the proposed artificial model. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]