Abstract
The continuous monitoring of power system devices is an important step toward keeping such capital assets safe. Partial discharge (PD)-based measurement tools provide a reliable and accurate condition assessment of power system insulations. It is very common that voids or cavities exist in every solid dielectric insulation medium. In this article, different voids are modeled and analyzed using an advanced finite element (FE)-based computational algorithm. The proposed approach can be used to measure PD in cavities and voids regardless of their shape and size. The frequentative scripting approach with finite element modeling (FEM) provides the results which satisfy all PD conditions. PD behavior has been studied and analyzed through PD statistical features obtained from the simulated PD signal. A comparative study between simulated and experimental results is also performed to validate the accuracy of the proposed modeling approach. To further improve the accuracy of the model, the influence and optimization of certain free parameters required for modeling has been carried out. The article shows how PD is greatly influenced by the shape and size of voids in dielectric insulators. The research realized in this article further provides the PD statistical features and its variation with respect to void shape and size. These features are utilized for the assessment of insulation quality. The variation in PD parameters with respect to voltage level is also presented and discussed.
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
no. 70,
pages 1 - 6,
ISSN: 0018-9456 - Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Qasim K., Refaat S., Abu-Rub H., Toliyat A., Olesz M., Darwish A.: Characterization of Defects Inside the Cable Dielectric With Partial Discharge Modeling// IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT -Vol. 70, (2020), s.1-6
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/tim.2020.3027925
- Sources of funding:
-
- 10.13039/100008982-NPRP through the Qatar National Research Fund (a member of Qatar Foundation);
- Verified by:
- Gdańsk University of Technology
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