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Transients Fault Analysis based on the Wavelet Transform for Fault Identification and Protection on Cycloconverter based High Voltage Low Frequency Transmission System

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posted on 2018-01-15, 13:25 authored by Dhrgham Mousa Jwad
This thesis presents a study on HVLF AC transmission systems for a long distance Offshore Wind Farm (OWF) grid connection. A particular scheme highlights the use of a high voltage cycloconverter as a frequency changer at the sending end of the transmission system, in which the voltage is stepped up at 60 Hz before inputting to the cycloconverter. This eliminates the need for a high voltage low frequency transformer on the offshore platform, and also it allows the use of standard 50/60 Hz generating equipment in the wind turbines. A modelling study has been undertaken to validate the operation of the system, including with the presence of transmission line faults. The study shows the effects of the pre-fault harmonics generated by the cycloconverter on the fault generated transients. Thus, the need to develop a new frequency based fault protection system for HVLF transmission is addressed. New transmission line fault detection and location algorithms for the HVLF system have been developed. Firstly, the frequency range of the post-fault generated transients were identified using Fast Fourier Transform (FFT) analysis. It was shown that these transient components, ranging from DC to high frequency, are distributed throughout the spectrum of the three-phase current signals. However, the FFT analysis provides the frequency information of these transients but without time information. In this thesis, the Wavelet Packets Transform (WPT) is introduced for the fault identification. The fault generated transients were detected by monitoring wavelet coefficients over a time window. The performance of the protection system under all possible fault scenarios of the HVLF transmission line are investigated. Finally, practical considerations, such as the impact of the fault inception angle and the switching and control of the cycloconverter on the fault detection and location algorithm’s accuracy were also investigated.

History

Supervisor(s)

Lefley, Paul; Ji, Bing

Date of award

2017-12-15

Author affiliation

Department of Engineering

Awarding institution

University of Leicester

Qualification level

  • Doctoral

Qualification name

  • PhD

Language

en

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