George R. S. Lira

Self-organizing maps applied to monitoring and diagnosis of ZnO surge arresters

In this work a monitoring and diagnostic technique for ZnO surge arresters is proposed. This technique is based on a special kind of Artificial Neural Network (ANN) known as Self-Organizing Maps (SOM), which is a network, trained using unsupervised learning. The proposed technique performs the thermal profile analysis of ZnO surge arresters when submitted to their operating voltage. From this analysis, the SOM network can determine the status of the surge arrester. So, this technique may be a very useful tool to power system utilities in their predictive monitoring activities, as well as to the manufactures, assisting the project of more robust surge arresters.

MOSA Monitoring Technique Based on Analysis of Total Leakage Current

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.

A low cost power quality meter over the internet

This paper proposes a low cost three-phase power quality meter. Due to its characteristics, the meter can be applied for residential or small businesses use. The proposed device uses the power definitions from IEEE Standard 1459-2010. Moreover, it calculates the true rms value, the individual harmonics, and the voltage unbalanced factor. In order to validate the power quality meter, simulations and experimental results are presented. The results are presented on a web page that can be accessed by any device with internet access.

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

A mathematical modeling procedure for single phase low power transformers is presented in this paper. It is based on the frequency response of the shunt parameters, taken from the electric model. The open circuit test was performed for different frequencies in four transformers, and the magnetizing parameter frequency responses were determined. It was verified that the sum of exponential functions can be employed to represent the behavior of the magnetizing parameters as a function of frequency, with notable accuracy. The results contribute to the improvement of mathematical models and circuit equivalents of single phase transformers.

Performance evaluation of MOSA models against lightning discharges

In this work a study about the performance of some metal oxide surge arrester models under lightning conditions is presented. Real data were used in electrical power system simulations. Part of the local utility system was chosen to receive the lightning discharges. Discharges with 8/20 µs and 1/2 µs were applied in the evaluated system. The evaluated surge arrester models presented similar results for 8/20 µs discharges, once that they were fitted for this kind of transient. However, for 1/2 µs discharges substantial differences were obtained, mainly, between the dynamic models and the conventional model. For this kind of discharge the dynamic models have shown plausible results.