This paper presents an electric model of a metal-oxide surge arrester (MOSA). The proposed electric model accurately represents the MOSA in a wide range of frequencies and amplitudes. The model was developed and validated based on MOSA electrical behavior in each one of the three operating regions of the zinc-oxide (ZnO) surge arresters, and in a database composed of voltage and current waveforms measured from tests performed in 12 ZnO varistors having different physical dimensions and electrical characteristics-from five different manufacturers. These varistors were subjected to different voltage levels in the low current region, and multilevel amplitude of switching current impulses (30/60 μs), lightning current impulses (8/20 μs), high current impulses (4/10 μs), and fast-front current impulses (1.5/26 μs and 3/6 μs) encompass the three regions of operation and a wide range of frequencies and amplitudes. The results provided by the MOSA wide-range (MWR) model were compared with those obtained in the laboratory. The MWR model has shown good agreement in terms of waveform, peak value, and absorbed energy for the evaluated cases.

Currently, the majority of metal-oxide surge arrester (MOSA) monitoring techniques are based on total leakage current decomposition of their capacitive and resistive components. However, these techniques are subject to some financial, technical, and practical limitations, which can hamper their usage on the field. In this paper, a new monitoring technique for the zinc-oxide surge arrester is proposed. The technique is based on the feature extraction of measured total current signals and on the analysis of these characteristics by artificial neural networks. The measured total currents were obtained from station class surge arresters submitted to their maximum continuous operating voltage. In the lab tests, six different kinds of failures were simulated on the tested MOSA with the purpose of evaluating the capacity of the technique to distinguish different operating conditions of surge arresters. Hit ratios greater than 98% were obtained in the identification of the operating conditions. The results show the viability of the technique on MOSA monitoring procedures.

MODELAGEM MATEMÁTICA DE TRANSFORMADORES BASEADA NA RESPOSTA EM FREQUÊNCIA DOS PARÂMETROS DE MAGNETIZAÇÃO

Electrical insulators are components used to promote electrical isolation and mechanical support for conductors in transmission lines belonging to the electric power systems (EPS). The performance of glass insulators is compromised mainly in the face of high pollution level, causing the amplitude of the leakage current to increase and the formation of superficial discharges. In this work, a methodology for estimating the surface pollution critical level of glass insulators using leakage current parameters and artificial intelligence algorithms is proposed. For this purpose, glass insulators were tested in the laboratory to simulate different levels of pollution, in order to record leakage current, voltage signals and environmental variables (e.g., humidity and temperature). The pollution level was simulated by depositing the pollution solution on the insulators, where each solution was differentiated based on the level of equivalent salt deposit density (ESDD). In the tests, the level of ESDD responsible for causing surface discharges was also recorded, as this phenomenon occurs at high levels of pollution. Pollution modeling was performed using forecasting algorithms such as multilayer perceptron (MLP) and support vectors regression (SVR). Based on the application of the best performance model and using criteria that indicate the occurrence of surface discharges, it was possible to estimate the critical level of pollution in the glass insulators string for 69 kV systems.

Several models were successfully developed to reproduce the dynamic behavior of ZnO surge arrester, but the accuracy and reliability of these models are only evaluated for residual voltage calculations. This paper presents a model developed with the specific goal of achieving reliable and accurate modeling of the energy absorbed by a ZnO surge arrester during impulsive transients. To develop and test the model, an experimental database was built, composed of responses of ZnO varistors to current impulses. The database contains the response of varistors of different classes and manufacturers, subjected to current impulses with different waveforms and amplitudes. Then, using system identification techniques, a mathematical model was proposed and validated. The proposed model was successfully tested on the same circumstances that traditional models are used and its performance was compared with the most relevant existing ZnO model. The results indicate that the developed model is an overall valid model for ZnO surge arresters and that energy calculations performed with it are more accurate and reliable.