Search

The most monitoring techniques of metal oxide surge arresters are based on harmonics analysis of resistive leakage current. Therefore, the extraction of resistive component from total leakage current is required. Up to now, several methods have been proposed for resistive leakage current extraction such as time-delay addition method. This method is only able to separate accurate resistive component under pure sinusoidal applied voltage. An improved time-delay addition method is proposed in this paper which is able to extract surge arrester resistive component under applied harmonic voltage. To accomplish this purpose, experimental tests have been performed on 20 kV surge arrester and obtained voltage and leakage current signals have been applied to the proposed and previous algorithms for resistive component extraction. In addition to investigate the ability of proposed algorithm, a typical surge arrester has been simulated in ATP-EMTP software and total leakage currents have been applied to both algorithms for resistive leakage current extraction. Results show that the proposed method is able to extract resistive component under applied harmonic voltage more accurate than previous one. Therefore, it is an improvement with respect to previous one that only works for sinusoidal voltage. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to estimate power loss characteristics of metal oxide surge arresters. The method was used to compute surge arrester power loss curve based on adaptive network based fuzzy inference system (ANFIS) and artificial neural network (ANN). Surge arrester operating history is an important factor that bears influence on its power loss. Degradation was, in this paper, introduced as a new index to represent operating history of metal oxide surge arrester. Therefore, applied voltage, temperature and degradation factor were considered as inputs in ANFIS system and ANN models to obtain accurate power loss which is a very important factor in surge arrester thermal stability. Degrading effect was undertaken by measurement voltage and current in varistors degraded by utilization in network. The results of the two artificial models were compared. Results show that ANFIS was more accurate than ANN. This study shows that the power loss characteristics of surge arrester are to a great extent accurately predictable using proposed artificial model. [ABSTRACT FROM AUTHOR]

ABSTRACT Analysis of electro-thermal behavior in various operating condition based on finite element method was proposed in this article. Power frequency and impulse stresses vary the operating region and temperature of surge arresters. Therefore, adaptive power loss was considered as a source in the modeling of surge arrester based on finite element method. Adaptive network based fuzzy inference system and frequency dependent model were used to model power loss in low and high current regions, respectively. To obtain accurate power loss, which is very important factor in electro-thermal analysis, applied voltage and temperature were considered as inputs in adaptive network based fuzzy inference system model. The experimental setup including impulse generator, power frequency high voltage generator and also an oven was arranged to achieve real data. Finally, the results of simulation based on proposed adaptive method were compared with the thermal infrared camera results. This study shows that the electro-thermal behavior of surge arrester is predictable with a good accuracy by using artificial model. © 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:910-920, 2015; View this article online at ; DOI [ABSTRACT FROM AUTHOR]

This paper presents proper indicators for evaluation of the surge arrester condition based on the leakage current analysis. Maximum amplitude of fundamental harmonic of the resistive leakage current ( I mr1 ), maximum amplitude of third harmonic of the resistive leakage current ( I mr3 ) and maximum amplitude of fundamental harmonic of the capacitive leakage current have been used as indicators for surge arrester condition monitoring. The effects of operating voltage fluctuation, third order of voltage harmonic, over-voltage and varistor aging have been investigated to show the ability of introduced indicators for accurate diagnostic of arrester’s conditions. In order to have accurate values of stray capacitors, 3D-FEM has been used. Moreover, surge arrester model for calculating leakage current has been performed in ATP–EMTP. In addition, the signal processing has been done using MATLAB software. This study shows that the introduced indicators are proper criteria for surge arrester condition monitoring. [ABSTRACT FROM AUTHOR]