This thesis deals with the online measurement of partial discharge (PD) in a high-voltage direct current (HVDC) converter station. The HVDC station is a particularly challenging environment for PD measurement due to elevated interference levels caused from the switching of the thyristor-controlled converters. Online PD measurements are performed on two specimens, one is an HVDC converter transformer and the other an HVDC converter wall bushing. The measurements are performed in the high-frequency range between 400-kHz to 30-MHz with a modern PD measurement instrument that employs a signal processing technique known as feature extraction. The results demonstrate that online measurement of PD in an HVDC station environment is possible. Input filtering and feature extraction methods can mitigate the converter interference. The feature extraction methods can also isolate individual PD phenomena, and allow for the trending and monitoring of insulation degradation. Furthermore, specific strategies for PD measurement and analysis are developed.

This thesis deals with the online measurement of partial discharge (PD) in a high-voltage direct current (HVDC) converter station. The HVDC station is a particularly challenging environment for PD measurement due to elevated interference levels caused from the switching of the thyristor-controlled converters. Online PD measurements are performed on two specimens, one is an HVDC converter transformer and the other an HVDC converter wall bushing. The measurements are performed in the high-frequency range between 400-kHz to 30-MHz with a modern PD measurement instrument that employs a signal processing technique known as feature extraction. The results demonstrate that online measurement of PD in an HVDC station environment is possible. Input filtering and feature extraction methods can mitigate the converter interference. The feature extraction methods can also isolate individual PD phenomena, and allow for the trending and monitoring of insulation degradation. Furthermore, specific strategies for PD measurement and analysis are developed.

In this study, the electrical aging of 15 kV Ethylene Propylene Rubber (EPR) power cables, located in PVC pipes containing water, was conducted by ac voltage with switching impulses superimposed. The experiments provided a better understanding of the electrical aging phenomenon of EPR cable insulation. They also helped to assess the reliability of EPR cables used under such circumstances. EPR cable insulation was aged by rated ac voltage with switching impulses superimposed. The experiments also examined the degradation of EPR insulation by elevated ac voltage with switching impulses superimposed. Partial discharge parameters, capacitance and dissipation factor were measured at subsequent intervals during the aging process so as to understand the factors affecting aging process. After completion of the aging study, the remaining dielectric strength of tested cables was evaluated by ac breakdown voltage measurement.

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A growing trend in the electrical industry is to move away from overhead lines and towards underground distribution. The cables necessary for underground distribution are stressed in various ways, and one of the most ignored stresses is that of overvoltage caused by switching. The focus of this research is to determine the effects that high voltage switching impulses have on the electrical strength of medium voltage cable insulation. Accelerated aging was performed on multiple samples of XLPE and EPR cables by applying multitudes of switching impulses. At various stages of the aging process, partial discharge measurements were taken. At the end of the aging process, the ac breakdown voltage of each cable sample was determined. While more testing is necessary to gain a greater understanding of this subject, the results obtained in this study show that switching impulses weaken cable insulation, which may lead to premature failure of distribution cables.

Design, development, and testing of a comprehensive and automated classification system for single and multiple PD source identification based on the relationship between the variation of PRPD patterns and the sources of PD is proposed. The proposed system consists of feature extraction methods and classifier algorithms that are implemented for recognition of partial discharge patterns. For single PD source identification, twelve high performance, applicable feature extraction techniques on PRPD patterns are employed to extract features. In order to present a comprehensive classification system, 10 well-known algorithms for the classification of PD sources have then been used. To evaluate the performance of the classification system, three laboratory test setups are designed and built to simulate various types of PD activities. The first test setup is designed to model common sources of PD in air, oil, and SF6. Using this setup, the application of automated classification system on different sources of PD in different HV insulation media is investigated. The second and third test setups are designed to test the classification system on identification of different sources of PD in oil-immersed insulation and power transformer cellulose insulation under both electrical and thermal stresses, respectively. In many practical situations, the interest lies in the identification of multiple, simultaneously activated PD sources in insulation. Multi-source PDs sometimes results in partially overlapped patterns, which makes them hard to be identified by single source identification techniques. To further enhance the proposed classification system, a novel algorithm to identify Multi-source PDs is developed and appended to the system. To evaluate the performance of this algorithm, a number of multi-source PD models have been designed. The overall results show that the classification system is well able to identify the single and multi-source of partial discharges. More importantly, this identification system is able to assign a ``degree of membership" to each PRPD pattern, besides assigning a class label to it. This enables probabilistic interpretation of a new PRPD pattern that is being classified and results in safer decision making based on the risk associated with different sources of PD. The results of this research is beneficial for the design of a solid basis for an automated, continuous 24/7 monitoring of equipment, which facilitates PD source identification in early stages and safe operation of HV apparatus. / October 2016

Electrical insulation under high voltage can eventually fail, causing critical damage to electronics. Such electrostatic discharge (ESD) is the primary source of anomalies or failures on spacecraft due to charged particles from the Sun or planetary radiation belts accumulating in spacecraft insulators. Highvoltage direct current power distribution is another example of a growing industry that needs to estimate the operational lifetime of electrical insulation. My research compares laboratory tests of ESD events in common insulating materials to a physics-based model of breakdown. This model of breakdown is based on the approximation that there are two primary types of defects in structurally amorphous insulators. One of the two defect modes can switch on and off depending on the material temperature. This dual-defect model can be used to explain both ESD and less-destructive transient partial discharges. I show that the results of ESD tests agree reasonably well with the dual defect model. I also show that transient partial discharges, which are usually ignored during ESD tests, are closely related to the probability of catastrophic ESD occurring. Since many partial discharges are typically seen during one ESD test, this relationship suggests that the measurements of partial discharges could accelerate the testing needed to characterize the likelihood of ESD in insulating materials.

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