Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 1272-1277 |
| Seitenumfang | 6 |
| Fachzeitschrift | IET Conference Proceedings |
| Jahrgang | 2023 |
| Ausgabenummer | 46 |
| Publikationsstatus | Veröffentlicht - 2023 |
| Veranstaltung | 23rd International Symposium on High Voltage Engineering, ISH 2023 - Glasgow, Großbritannien / Vereinigtes Königreich Dauer: 28 Aug. 2023 → 1 Sept. 2023 |
Abstract
Due to the increasing importance of high voltage DC components in the transmission systems, HVDC-specific diagnostic methods will become indispensable. In AC systems it is possible to perform a partial discharge diagnostic analysis about the nature of the fault based on the way and the phase angle in which partial discharges occur. Unfortunately, a similar technique is, due to the lack of angular references and time invariability in the case of HVDC systems, impossible. Based on these considerations a method based on a wavelet packet decomposition for the classification of partial discharges is presented in this contribution. Partial discharges were induced and measured in models of typical faults in solid insulation systems in two different polymeric solid insulation materials. Special test sequences optimized to reduce the influence of space charges and to analyse the influence of the voltage and the test period as well as the type of used measurement bandwidth were implemented. The use of the investigated method shows a good performance in classifying partial discharge sources, which demonstrates the potential of wavelet packet decomposition for the development of diagnostic tools.
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in: IET Conference Proceedings, Jahrgang 2023, Nr. 46, 2023, S. 1272-1277.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - CLASSIFICATION OF PARTIAL DISCHARGE SOURCES UNDER DC VOLTAGE BY WAVELET DECOMPOSITION
AU - Torres, Javier
AU - Stahl, Laureen
AU - Werle, Peter
N1 - Publisher Copyright: © The Institution of Engineering & Technology 2023.
PY - 2023
Y1 - 2023
N2 - Due to the increasing importance of high voltage DC components in the transmission systems, HVDC-specific diagnostic methods will become indispensable. In AC systems it is possible to perform a partial discharge diagnostic analysis about the nature of the fault based on the way and the phase angle in which partial discharges occur. Unfortunately, a similar technique is, due to the lack of angular references and time invariability in the case of HVDC systems, impossible. Based on these considerations a method based on a wavelet packet decomposition for the classification of partial discharges is presented in this contribution. Partial discharges were induced and measured in models of typical faults in solid insulation systems in two different polymeric solid insulation materials. Special test sequences optimized to reduce the influence of space charges and to analyse the influence of the voltage and the test period as well as the type of used measurement bandwidth were implemented. The use of the investigated method shows a good performance in classifying partial discharge sources, which demonstrates the potential of wavelet packet decomposition for the development of diagnostic tools.
AB - Due to the increasing importance of high voltage DC components in the transmission systems, HVDC-specific diagnostic methods will become indispensable. In AC systems it is possible to perform a partial discharge diagnostic analysis about the nature of the fault based on the way and the phase angle in which partial discharges occur. Unfortunately, a similar technique is, due to the lack of angular references and time invariability in the case of HVDC systems, impossible. Based on these considerations a method based on a wavelet packet decomposition for the classification of partial discharges is presented in this contribution. Partial discharges were induced and measured in models of typical faults in solid insulation systems in two different polymeric solid insulation materials. Special test sequences optimized to reduce the influence of space charges and to analyse the influence of the voltage and the test period as well as the type of used measurement bandwidth were implemented. The use of the investigated method shows a good performance in classifying partial discharge sources, which demonstrates the potential of wavelet packet decomposition for the development of diagnostic tools.
KW - HVDC
KW - PARTIAL DISCHARGES
KW - PD IDENTIFICATION
KW - WAVELET
UR - http://www.scopus.com/inward/record.url?scp=85203344246&partnerID=8YFLogxK
U2 - 10.1049/icp.2024.0799
DO - 10.1049/icp.2024.0799
M3 - Conference article
AN - SCOPUS:85203344246
VL - 2023
SP - 1272
EP - 1277
JO - IET Conference Proceedings
JF - IET Conference Proceedings
SN - 2732-4494
IS - 46
T2 - 23rd International Symposium on High Voltage Engineering, ISH 2023
Y2 - 28 August 2023 through 1 September 2023
ER -