An electric power system consists of the generating stations, the transmission
lines, and the distribution systems. Transmission lines are the connecting links
between the generating stations and the distribution systems. With the rapid
growth of economy and technology, the demand for large blocks of power,
power quality and increased reliability suggested the interconnection of
neighboring systems. Transmission lines are elements of a network which
connects the generating plants to the distribution systems, and could extend
hundreds of miles . Because of the long distances traversed by transmission
lines over open area, they tend to fade by natural and artificial calamity imposed
on the power system. It maybe easy to discover the fault with sufficient
information in the populous region. When fault occurs in the remote region, it is
difficult to identify the outage location. An efficient and reliable technique is
thus desirable to resolve the problem.
This dissertation presents the fault location for high voltage lines with
Artificial Neural Network( ANN ) method. Beside the fault location, this
research also improve the problem further by considering the fault resistance.
The fault resistance may not remain the same due to the variation of
environmental factors. The fault location may involve errors owing to the fault
resistance. An algorithms has been developed in this dissertation to calculate
fault resistance and revise the ANN training data for three-phase fault, double
line-to-ground fault, single line-to-ground fault, and line-to-line fault. To verify
the effectiveness of the method, practical transmission lines were used for tests.
The results proved that the method could be used to identify the fault location
effectively and help dispatchers determine a reference distance.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0621100-152324 |
| Date | 21 June 2000 |
| Creators | lin, chia-hung |
| Contributors | Whei-Min Lin, Wen-chen chu, Ming-Tong Tsay, Ta-Peng Taso, Hong-ter Yang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0621100-152324 |
| Rights | off_campus_withheld, Copyright information available at source archive |
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