Title :
Integrating the S-PQDA software tool in the utility power quality management system
Author :
Faisal, M.F. ; Mohamed, A.
Author_Institution :
Tenaga Nasional Berhad, Petaling Jaya, Malaysia
Abstract :
This paper presents a smart power quality data a analyzer (S-PQDA) or power quality diagnosis software (PQDS) tool that performs power quality (PQ) diagnosis on the PQ disturbance data recorded by an online PQ monitoring system. The software tool enables power utility engineers to perform automatic PQ disturbance detection, classification and diagnosis of the disturbances. The PQDS also assists the power utility engineers in identifying the existence of incipient faults due to partial discharges in the cable compartment. The overall accuracy of the software in performing PQ diagnosis is 96.4%.
Keywords :
data analysis; fault diagnosis; partial discharges; power cables; power engineering computing; power supply quality; power system management; power system measurement; software tools; S-PQDA software tool; incipient faults; online PQ monitoring system; partial discharges; power cable compartment; power management system; power quality diagnosis software; power utility; smart power quality data analyzer; Feature extraction; Graphical user interfaces; Monitoring; Power quality; Signal processing; Substations; Voltage fluctuations; artificial intelligence; incipient faults; power quality; signal processing;
Conference_Titel :
Electric Machines & Drives Conference (IEMDC), 2011 IEEE International
Conference_Location :
Niagara Falls, ON
Print_ISBN :
978-1-4577-0060-6
DOI :
10.1109/IEMDC.2011.5994947
