Detection, Localization, and Recognition of Faults in Transmission Networks Using Transient Currents
| dc.contributor.author | Perera, Nuwan | |
| dc.contributor.examiningcommittee | Sidhu, Tarlochan(University of Ontario Institute of Technology) Gole,Aniruddha(Electrical and Computer Engineering) Rattanawangcharoen, Nipon(Civil Engineering) | en_US |
| dc.contributor.supervisor | Rajapakse, Athula (Electrical and Computer Engineering) | en_US |
| dc.date.accessioned | 2012-09-18T16:06:09Z | |
| dc.date.available | 2012-09-18T16:06:09Z | |
| dc.date.issued | 2012-09-18 | |
| dc.degree.discipline | Electrical and Computer Engineering | en_US |
| dc.degree.level | Doctor of Philosophy (Ph.D.) | en_US |
| dc.description.abstract | The fast clearing of faults is essential for preventing equipment damage and preserving the stability of the power transmission systems with smaller operating margins. This thesis examined the application of fault generated transients for fast detection and isolation of faults in a transmission system. The basis of the transient based protection scheme developed and implemented in this thesis is the fault current directions identified by a set of relays located at different nodes of the system. The direction of the fault currents relative to a relay location is determined by comparing the signs of the wavelet coefficients of the currents measured in all branches connected to the node. The faulted segment can be identified by combining the fault directions identified at different locations in the system. In order to facilitate this, each relay is linked with the relays located at the adjacent nodes through a telecommunication network. In order to prevent possible malfunctioning of relays due to transients originating from non-fault related events, a transient recognition system to supervise the relays is proposed. The applicability of different classification methods to develop a reliable transient recognition system was examined. A Hidden Markov Model classifier that utilizes the energies associated with the wavelet coefficients of the measured currents as input features was selected as the most suitable solution. Performance of the protection scheme was evaluated using a high voltage transmission system simulated in PSCAD/EMTDC simulation software. The custom models required to simulate the complete protection scheme were implemented in PSCAD/EMTDC. The effects of various factors such as fault impedance, signal noise, fault inception angle and current transformer saturation were investigated. The performance of the protection scheme was also tested with the field recorded signals. Hardware prototypes of the fault direction identification scheme and the transient classification system were implemented and tested under different practical scenarios using input signals generated with a real-time waveform playback instrument. The test results presented in this thesis successfully demonstrate the potential of using transient signals embedded in currents for detection, localization and recognition of faults in transmission networks in a fast and reliable manner. | en_US |
| dc.description.note | October 2012 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/8867 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | wavelet transform | en_US |
| dc.subject | transmission line | en_US |
| dc.subject | power system protection | en_US |
| dc.subject | transient protection | en_US |
| dc.subject | travelling wave | en_US |
| dc.subject | Hidden Markov Model classifier | en_US |
| dc.title | Detection, Localization, and Recognition of Faults in Transmission Networks Using Transient Currents | en_US |
| dc.type | doctoral thesis | en_US |