A new technique to predict the sources of voltage sags using support vector regression based S-transform

Mohamed Fuad Faisal, Azah Mohamed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The concern on the quality of electrical power has become an issue amongst many electricity users around the world. When the quality of the power supply is not good, it may results in malfunction of sensitive equipments in industrial plants. It is imperative that all the power quality disturbances must be accurately detected, classified and diagnosed so that proper mitigation measures can be implemented. In this paper a new technique using the S-transform and the Support Vector Regression (SVR), was developed for diagnosing the sources of the voltage sags. The new technique was tested on 40 numbers of voltage sags and yielded satisfactory results in the prediction of sources of voltage sags. The proposed SVR based S-transform technique was also more superior than that of the learning vector quantization (LVQ) based S-transform technique.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009
Publication statusPublished - 2009
EventIASTED International Conference on Modelling, Simulation, and Identification, MSI 2009 - Beijing
Duration: 12 Oct 200914 Oct 2009

Other

OtherIASTED International Conference on Modelling, Simulation, and Identification, MSI 2009
CityBeijing
Period12/10/0914/10/09

Fingerprint

S-transform
Voltage Sag
Support Vector Regression
Mathematical transformations
Predict
Electric potential
Vector quantization
Power quality
Learning Vector Quantization
Power Quality
Industrial plants
Electricity
Disturbance
Prediction

Keywords

  • Power quality
  • S-transform
  • SVM
  • SVR
  • Voltage sags

ASJC Scopus subject areas

  • Applied Mathematics
  • Logic
  • Modelling and Simulation

Cite this

Faisal, M. F., & Mohamed, A. (2009). A new technique to predict the sources of voltage sags using support vector regression based S-transform. In Proceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009

A new technique to predict the sources of voltage sags using support vector regression based S-transform. / Faisal, Mohamed Fuad; Mohamed, Azah.

Proceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009. 2009.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Faisal, MF & Mohamed, A 2009, A new technique to predict the sources of voltage sags using support vector regression based S-transform. in Proceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009. IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009, Beijing, 12/10/09.
Faisal MF, Mohamed A. A new technique to predict the sources of voltage sags using support vector regression based S-transform. In Proceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009. 2009
Faisal, Mohamed Fuad ; Mohamed, Azah. / A new technique to predict the sources of voltage sags using support vector regression based S-transform. Proceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009. 2009.
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