Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique

Ahmed Hussain Elmetwaly; Abdelazeem Abdallah Abdelsalam; Azza Ahmed Eldessouky; Abdelhay Ahmed Sallam

doi:doi:10.11648/j.epes.20150401.11

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Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique

Ahmed Hussain Elmetwaly, Abdelazeem Abdallah Abdelsalam, Azza Ahmed Eldessouky, Abdelhay Ahmed Sallam

Published in American Journal of Electrical Power and Energy Systems (Volume 4, Issue 1)

Received: 5 February 2015 Accepted: 15 February 2015 Published: 2 March 2015

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Abstract

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.

Published in	American Journal of Electrical Power and Energy Systems (Volume 4, Issue 1)
DOI	10.11648/j.epes.20150401.11
Page(s)	1-9
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Power Quality, S-Transform, Fuzzy Expert System

References

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[7]	Abdelazeem A. Abdelsalama, Azza A .Eldesouky, and Abdelhay A. Sallam, “Classiﬁcation of power system disturbances using linear Kalman ﬁlter and Fuzzy-expert system,” Electr. Power Energy Syst., vol. 43, no. 1, pp. 688–695, 2012.
[8]	C. I. Chen, G. W. Chang, R. C. Hong, H. M. Li, “Extended real model of Kalman ﬁlter for time-varying harmonics estimation,” IEEE Trans Power Deliv., vol. 25, no. 1, pp. 17–26, 2010.
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APA Style

Ahmed Hussain Elmetwaly, Abdelazeem Abdallah Abdelsalam, Azza Ahmed Eldessouky, Abdelhay Ahmed Sallam. (2015). Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique. American Journal of Electrical Power and Energy Systems, 4(1), 1-9. https://doi.org/10.11648/j.epes.20150401.11

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ACS Style

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. Am. J. Electr. Power Energy Syst. 2015, 4(1), 1-9. doi: 10.11648/j.epes.20150401.11

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AMA Style

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. Am J Electr Power Energy Syst. 2015;4(1):1-9. doi: 10.11648/j.epes.20150401.11

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@article{10.11648/j.epes.20150401.11,
  author = {Ahmed Hussain Elmetwaly and Abdelazeem Abdallah Abdelsalam and Azza Ahmed Eldessouky and Abdelhay Ahmed Sallam},
  title = {Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {4},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.epes.20150401.11},
  url = {https://doi.org/10.11648/j.epes.20150401.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20150401.11},
  abstract = {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.},
 year = {2015}
}

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TY  - JOUR
T1  - Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique
AU  - Ahmed Hussain Elmetwaly
AU  - Abdelazeem Abdallah Abdelsalam
AU  - Azza Ahmed Eldessouky
AU  - Abdelhay Ahmed Sallam
Y1  - 2015/03/02
PY  - 2015
N1  - https://doi.org/10.11648/j.epes.20150401.11
DO  - 10.11648/j.epes.20150401.11
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20150401.11
AB  - 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.
VL  - 4
IS  - 1
ER  -

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Author Information

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

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APA Style

Ahmed Hussain Elmetwaly, Abdelazeem Abdallah Abdelsalam, Azza Ahmed Eldessouky, Abdelhay Ahmed Sallam. (2015). Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique. American Journal of Electrical Power and Energy Systems, 4(1), 1-9. https://doi.org/10.11648/j.epes.20150401.11

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ACS Style

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. Am. J. Electr. Power Energy Syst. 2015, 4(1), 1-9. doi: 10.11648/j.epes.20150401.11

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AMA Style

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. Am J Electr Power Energy Syst. 2015;4(1):1-9. doi: 10.11648/j.epes.20150401.11

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@article{10.11648/j.epes.20150401.11,
  author = {Ahmed Hussain Elmetwaly and Abdelazeem Abdallah Abdelsalam and Azza Ahmed Eldessouky and Abdelhay Ahmed Sallam},
  title = {Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {4},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.epes.20150401.11},
  url = {https://doi.org/10.11648/j.epes.20150401.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20150401.11},
  abstract = {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.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Detection and Identification of PQ Disturbances Using S-Transform and Artificial Intelligent Technique
AU  - Ahmed Hussain Elmetwaly
AU  - Abdelazeem Abdallah Abdelsalam
AU  - Azza Ahmed Eldessouky
AU  - Abdelhay Ahmed Sallam
Y1  - 2015/03/02
PY  - 2015
N1  - https://doi.org/10.11648/j.epes.20150401.11
DO  - 10.11648/j.epes.20150401.11
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20150401.11
AB  - 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.
VL  - 4
IS  - 1
ER  -

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