The increased need for electric power combined with an aging underground cable infrastructure in a deregulated market environment have forced utilities to refocus their attention on reliability while at the same time reducing maintenance costs as much as possible. This has created a significant need for diagnostic methods and technologies to assess the condition of the underground cable systems. However, while several cable diagnostic technologies are available, they have not all yet been fully accepted in the United States. This is because the different technologies lead to different conclusions for the same cable system, and thus utilities do not completely trust the conclusions. A better understanding of the diagnostic technologies and their correct application is therefore required.
The most widely used diagnostic technologies in the United States include dissipation factor (Tan-delta and partial discharge measurements; these tests are therefore, the main focus of this thesis; in particular, when applied to underground extruded cable systems. The purpose of this research is to advance the field of characterization of power cable defects by addressing a number of theoretical and practical diagnostic measurements and their interpretation issues. The discussion is based on data from laboratory experiments and field tests.
This thesis consists of two major parts. The first part is devoted to the characterization by Tan-delta measurements in which the major contribution is a new approach for condition assessment using this technology. The second part is devoted to the work on characterization by partial discharge measurements, and the major contribution is a novel approach that is able to analyze, evaluate, and reduce the number of partial discharge diagnostic features.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/31841 |
Date | 03 November 2008 |
Creators | Hernández Mejía, Jean Carlos |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Dissertation |
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