DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-7, Issue-3 ( Mar, 2019 ) | |||||||||
Paper Title |
The Performance of Clustering Technique and Artificial Intelligence in Power System Fault Investigation | |||||||||
Author Name |
Amalina Abdullah | |||||||||
Affilition |
School of Electric and Electronic Engineering, University Science Malaysia, Penang, Malaysia | |||||||||
Pages |
59-64 | |||||||||
Abstract |
This paper studied the performance of clustering technique and artificial intelligence in power system fault investigation. The study looking forward pertinent to fault classification and fault location. In terms of clustering technique, the focus is on Gustafson-Kessel clustering algorithm. Where as the Adaptive Neuro-Fuzzy Inference System (ANFIS) is one of the technique in artificial intellkigence that believed to give a great performance. Both techniques were combined due to their advantages and tested using a number of cases pertinent to a few types of fault at power transmission line. This idea has potential to analyze the fault location without the knowledge of line parameters. The results show that the scheme can perform well and has a high percentage of accuracy. Keywords - Gustafson-Kessel Clustering Algorithm, Power Transmission Line, Adaptive Neuro-Fuzzy Inference System | |||||||||
| View Paper | ||||||||||
