A Neural Network Based Fault Locator Algorithm for Series Compensated Transmission Lines | ||||
| Port-Said Engineering Research Journal | ||||
| Article 10, Volume 19, Issue 2, September 2015, Page 87-95 PDF (850.95 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/pserj.2015.45866 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Sobhy serry; Heba Halim | ||||
| 1Electrical Engineering power Dept., Faculty of Engineering Port-Said University | ||||
| Abstract | ||||
| The electrical faults on transmission lines are detected and isolated by the system protective devices. Transmission lines with series compensators require more attention and special protection settings. Once the fault has been cleared, outage times can be reduced. This paper demonstrates the usage of artificial neural network (ANN) for extra high voltage (EHV) series compensated transmission line fault location. The results show that the proposed ANN is promising and very accurate for fault location estimation. Furthermore, the ANN for the compensated line by one three-phase bank has been presented. In addition, a new fault detection and location method have been extensively tested using MATLAB software for a 400-kV, 300-km transmission line. The results demonstrated a high accuracy and robustness of the ANN-based algorithm. Fault detection, types, locations, path resistances and the fault inception angles are studied. The different power system data currents, voltages, capacitances, angles and time constants of the sources are covered. Experimental results were provided to confirm the theoretical results which coincided perfectly together. The results of the present work were complied and clarified with other works. | ||||
| Keywords | ||||
| Artificial Neural Networks; Fault Detection; fault location; Series compensation; and transmission | ||||
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