Title :
Power system fault detection, classification and location using the K-Nearest Neighbors
Author :
Abdelmadjid Recioui;Brahim Benseghier;Hamza Khalfallah
Author_Institution :
Laboratory signals and systems, Institute of Electrical and Electronic Engineering, University of Boumerdes, Avenue de l´ind?pendance, 35000, Algeria
Abstract :
Power systems are frequently subjected to faults. These faults can cause the destruction of expensive power system components such as motors, generators, and transformers, explosions due to over-voltages, high currents, outage and death. A power protection system is required in order to detect, classify, and locate the fault to clear it rapidly and to minimize the effects mentioned before. This paper deals with the detection, classification and location of power system faults on the IEEE 14 Bus Test Network using the K-Nearest Neighbors based on MATLAB/SIMULINK.
Keywords :
"Circuit faults","Training","Power systems","Fault location","Support vector machines","Fault detection","Classification algorithms"
Conference_Titel :
Electrical Engineering (ICEE), 2015 4th International Conference on
DOI :
10.1109/INTEE.2015.7416832