Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667552
Title: Transient fault location in low voltage underground distribution networks
Author: Tao, Yuxian
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2013
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Abstract:
This thesis presents a novel approach to automatic transient fault location in Low Voltage Underground Distribution Networks (LVUDN). A transient fault is the first stage of development of a fault condition which is indicative of a threat to power network security, but is not significant enough to trip the protection system. The proposed approach is based on time domain reflectometry (TDR), enhanced by pulse compression, wavelet transform and adaptive filters. The thesis provides a review of the properties of faults in LVUDN and of the characteristics of typical underground cables used in LVUDN. Advantages and restrictions of existing fault location techniques were discussed. Advanced signal processing tools such as pulse compression, adaptive filter and wavelet transform were also investigated. A pulse compression enhanced TDR acquisition methodology was developed and a self-comparing scheme was proposed to detect the timely change of the enhanced TDR waveform, thereby providing the corresponding required deviation-threshold to trigger the system and finally to calculate the fault distance. The pulse-compression technique provides better resolution and detection range, and side lobes are suppressed by applying wavelet transform. The deviation trigger is further enhanced by adaptive filtering for better noise rejection. A fully-customised, prototype fault locator and software were developed to implement the pulse compression, wavelet transform and adaptive based automatic transient fault location system. The prototype fault locator was tested in a live LVUDN and the results were evaluated.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.667552  DOI: Not available
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