Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique
American Journal of Electrical Power and Energy Systems
Volume 4, Issue 1, January 2015, Pages: 1-9
Received: Feb. 5, 2015;
Accepted: Feb. 15, 2015;
Published: Mar. 2, 2015
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Ahmed Hussain Elmetwaly, Dept. of Electrical Engineering, El Shorouk Academy, Cairo, Egypt
Abdelazeem Abdallah Abdelsalam, Dept.of Electrical Engineering, Suez Canal University, Ismailia, Egypt
Azza Ahmed Eldessouky, Dept. of Electrical Engineering, Port-Said University, Port-Said, Egypt
Abdelhay Ahmed Sallam, Dept. of Electrical Engineering, Port-Said University, Port-Said, Egypt
This paper proposes a new technique based on S-transform time-frequency analysis and Fuzzy expert system for classifying power quality (PQ) disturbances. The S-transform is a new time frequency analysis method. It has the features of both continuous wavelet transform (CWT) and short time Fourier transform (STFT). Through S-transform time-frequency analysis, a set of feature components are extracted for identifying PQ disturbances such as; the amplitude of the S-transform matrix and the total harmonic distortion (THD). The two parameters are the inputs to Fuzzy-expert system that uses some rules on these inputs to characterize the PQ events in the captured waveform (e.g. sag, swell, interruption, surge, sag with harmonic and swell with harmonic). Several simulation using Matlab environment and practical data are used to validate the proposed technique. The results depict that the proposed technique has the ability to accurately identify and characterize PQ disturbances.
Ahmed Hussain Elmetwaly,
Abdelazeem Abdallah Abdelsalam,
Azza Ahmed Eldessouky,
Abdelhay Ahmed Sallam,
Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique, American Journal of Electrical Power and Energy Systems.
Vol. 4, No. 1,
2015, pp. 1-9.
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