Power Quality Detection and Classification Using S-Transform and Rule-Based Decision Tree

Salah J. Alqam, Fouad R. Zaro
2019 International Journal of Electrical and Electronic Engineering & Telecommunications  
This paper presents a method for detection of Power Quality (PQ) disturbances using Stockwell's transform. Modeling equations are used for PQ disturbance generation using MATLAB program as per IEEE standards. Signals features are extracted from the time-frequency analysis based on Stockwell's transform. A rule-based decision tree are used to classify various PQ disturbances. It can be seen that high efficiency of classification is achieved using S-transform with rule-based decision tree.
more » ... PQ disturbances are addressed with single and combined disturbances. Results demonstrate the accuracy and robustness of the proposed method in detection and recognition of single and combined PQ disturbances under noiseless and noisy conditions. The proposed algorithm also shows good performance in comparison with other reported studies.  Index Terms-feature extraction, MATLAB program, power quality disturbance, rule-based decision tree, Stockwell transform, time frequency analysis Salah J. Alqam has received his B.S. degree in electrical engineering from Birzeit University (BZU), Palestine in 1998. Currently, he is in the final semester of Joint master in electrical engineering (JMEE) program between Birzeit University, Palestine Polytechnic University and Europe Universities. He is interested in smart metering systems (AMI), smart grids, electrical distribution systems planning, operation and maintenance, and power quality. Dr. Fouad Zaro has received his B.S. degree in electrical engineering from Palestine Polytechnic University (PPU), Palestine. Later on, he received his M.S. and Ph.D. degrees in electrical engineering from King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia in 2010 and 2013, respectively. Since 2014 he is an assistant professor in Palestine Polytechnic University. He is interested in power quality, artificial intelligent techniques, power system planning and operation, FACTS devices, and smart grid.
doi:10.18178/ijeetc.8.1.45-50 fatcat:bbtiki63jvafjf32eksyfovbyy