Title :
A dependency model-based approach for identifying and evaluating power quality problems
Author :
Azam, Mohammad S. ; Tu, Fang ; Pattipati, Krishna R. ; Karanam, Rajaiah
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA
fDate :
7/1/2004 12:00:00 AM
Abstract :
The purpose of this paper is to present a diagnostic system that will not only monitor sensor data streams, but also classify power conditions, and diagnose power quality problems both in real-time and off-line. Signal processing techniques are applied to extract features from monitored data for event detection and classification. A cause-effect relationship model is used to trace the power quality related events to particular equipment of a system under consideration. The methodology has been implemented in a software tool. Results obtained from the application of this tool on monitored data collected from a facility validate the utility of this approach.
Keywords :
computerised monitoring; power engineering computing; power supply quality; signal processing; software tools; cause-effect relationship; dependency model-based approach; diagnostic system; event classification; event detection; feature extraction; power condition classification; power quality diagnostics; power quality evaluation; power quality identification; sensor data stream monitoring; signal processing technique; software tool; Condition monitoring; Data mining; Event detection; Feature extraction; Power quality; Power system modeling; Real time systems; Sensor systems; Signal processing; Software tools; Cause–effect relationships; DWT; Lagrangian relaxation; STFT; discrete wavelet transform; multiple fault diagnosis; power quality; real-time detection; reliability; set-covering; short-time Fourier transform; subgradient optimization;
Journal_Title :
Power Delivery, IEEE Transactions on
DOI :
10.1109/TPWRD.2003.822537
