A novel concept for power quality study is proposed. The concept integrates the power system modeling, classifying and characterizing of power quality events, studying equipment sensitivity to the event disturbance, and locating point of event occurrence into one unified frame. Both Fourier and wavelet analyzes are applied for extracting distinct features of various types of events as well as for characterizing the events. A new fuzzy expert system for classifying power quality events based on such features is presented with improved performance over previous neural network based methods. A novel simulation method is outlined for evaluating the operating characteristics of the equipment during specific events. A software prototype implementing the concept has been developed in MATLAB. The voltage sag event is taken as an example for illustrating the analysis methods and software implementation issues. It is concluded that the proposed approach is feasible and promising for real world applications.
|Number of pages||6|
|Journal||IEEE Transactions on Power Delivery|
|State||Published - Apr 2002|
Bibliographical noteFunding Information:
Manuscript received August 25, 1999. This work was supported by the Texas Higher Education Coordinating Board Advanced Technology Program and TXU Electric and Gas and Reliant Energy HL&P. M. Kezunovic is with the Department of Electrical Engineering, Texas A&M University, College Station, TX 77843-3128 USA. Y. Liao is with ABB Electric Systems Technology Institute, Raleigh, NC 27606 USA. Publisher Item Identifier S 0885-8977(02)00536-8.
- Pattern classification
- Power quality
- Signal processing
- Wavelet transforms
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering