A Novel Method for Online Diagnostic Analysis of Partial Discharge in Instrument Transformers and Surge Arresters from the Correlation of HFCT and IEC Methods

Marcel Antonionni de Andrade Romano (), André Melo de Morais, Marcus Vinicius Alves Nunes, Kaynan Maresch, Luiz Fernando Freitas-Gutierres, Ghendy Cardoso, Aécio de Lima Oliveira, Erick Finzi Martins, Cristian Hans Correa and Herber Cuadro Fontoura
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Marcel Antonionni de Andrade Romano: High and Extra High Voltage Laboratory, Institute of Technology, Federal University of Pará, Pará 66075-110, PA, Brazil
André Melo de Morais: High and Extra High Voltage Laboratory, Institute of Technology, Federal University of Pará, Pará 66075-110, PA, Brazil
Marcus Vinicius Alves Nunes: High and Extra High Voltage Laboratory, Institute of Technology, Federal University of Pará, Pará 66075-110, PA, Brazil
Kaynan Maresch: Laboratory for Analysis and Protection of Electrical Systems, Technology Center, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Luiz Fernando Freitas-Gutierres: Laboratory for Analysis and Protection of Electrical Systems, Technology Center, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Ghendy Cardoso: Laboratory for Analysis and Protection of Electrical Systems, Technology Center, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Aécio de Lima Oliveira: Laboratory for Analysis and Protection of Electrical Systems, Technology Center, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Erick Finzi Martins: Engineering Board, CPFL Transmission, Porto Alegre 90230-181, RS, Brazil
Cristian Hans Correa: Engineering Board, CPFL Transmission, Porto Alegre 90230-181, RS, Brazil
Herber Cuadro Fontoura: Engineering Board, CPFL Transmission, Porto Alegre 90230-181, RS, Brazil

Energies, 2024, vol. 17, issue 19, 1-20

Abstract: In this work, a new methodology is proposed for the online and non-invasive extraction of partial discharge (PD) pulses from raw measurement data obtained using a simplified setup. This method enables the creation of sub-windows with optimized size, each containing a single candidate PD pulse. The proposed approach integrates mathematical morphological filtering (MMF) with kurtosis, a first-order Savitzky-Golay smoothing filter, the Otsu method for thresholding, and a specific technique to associate each sub-window with the phase angle of the applied voltage waveform, enabling the construction of phase-resolved PD (PRPD) patterns. The methodology was validated against a commercial PD detection device adhering to the IEC (International Electrotechnical Commission) standard. Experimental results demonstrated that the proposed method, utilizing an off-the-shelf 8-bit resolution data acquisition system and a low-cost high-frequency current transformer (HFCT) sensor, effectively diagnoses and characterizes PD activity in high-voltage equipment, such as surge arresters and instrument transformers, even in noisy environments. It was able to characterize PD activity using only a few cycles of the applied voltage waveform and identify low amplitude PD pulses with low signal-to-noise ratio signals. Other contribution of this work is the diagnosis and fault signature obtained from a real surge arrester (SA) with a nominal voltage of 192 kV, corroborated by destructive disassembly and internal inspection of the tested equipment. This work provides a cost-effective and accurate tool for real-time PD monitoring, which can be embedded in hardware for continuous evaluation of electrical equipment integrity.

Keywords: partial discharge; pulse extraction; operating condition monitoring; surge arrester (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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