A spatial-correlated scheme for wavelet transform based power quality monitoring

Hong-Tzer Yang, Chiung Chou Liao

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

Abstract

The disturbance signal in a power system can be detected by comparing the wavelet transformed (WT) signal with an empirically given threshold. However, as the signal under analysis contains noises, especially the white noise with flat spectrum, the threshold is difficult. To enhance the WT technique in processing the noise-riding signals, this paper proposes a spatial-correlated noise-suppression algorithm. The abilities of the WT in detecting and localizing the disturbances can hence be restored. Finally, employed are the actual data obtained from the practical power systems of Taiwan Power Company (TPC) to test the effectiveness of the developed de-noising scheme.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing
EditorsH. Leung, H. Leung
Pages182-187
Number of pages6
Publication statusPublished - 2003 Dec 1
EventProceedings of the Seventh IASTED International Conference on Artificial Intelligence and Soft Computing - Banff, Canada
Duration: 2003 Jul 142003 Jul 16

Publication series

NameProceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing
Volume7

Other

OtherProceedings of the Seventh IASTED International Conference on Artificial Intelligence and Soft Computing
CountryCanada
CityBanff
Period03-07-1403-07-16

All Science Journal Classification (ASJC) codes

  • Development
  • Artificial Intelligence

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  • Cite this

    Yang, H-T., & Liao, C. C. (2003). A spatial-correlated scheme for wavelet transform based power quality monitoring. In H. Leung, & H. Leung (Eds.), Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing (pp. 182-187). (Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing; Vol. 7).