Power quality

Kyeon Hur, Surya Santoso

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Providing power quality (PQ) for 21st-century needs is one of the widely accepted principal characteristics of the envisioned Smart Grid because we will have more and more PQ-sensitive loads such as microprocessor-based devices, critical manufacturing processes, and data centers [1]. Our future global competitiveness demands disturbance-free operation of the digital devices that empower the productivity of our economy. It is expected that the Smart Grid will provide a reliable power supply with fewer and briefer outages, cleaner power, and self-healing power systems, through advanced PQ monitoring, analysis of the measurement data, diagnosis of PQ disturbances, identification of the root causes, and timely automated controls. Note that computational intelligence(CI) has been an integral, significant part of advancing and expanding the horizons of this PQ research. The capabilities and applications of CI for PQ are continually evolving due to advanced PQ monitoring (or recording) devices. The objective of this chapter is to present these CI applications such as signal processing and artificial intelligence (AI) techniques to help understand, measure, and mitigate PQ phenomena. This chapter also describes challenges and potential applications in turning raw PQ measurement data to a much more valuable and actionable knowledge in order to improve PQ performance and produce real financial benefits as well.

Original languageEnglish
Title of host publicationComputational Intelligence in Power Engineering
EditorsBijaya Ketan Panigrahi
Pages199-234
Number of pages36
DOIs
Publication statusPublished - 2010 Sep 23

Publication series

NameStudies in Computational Intelligence
Volume302
ISSN (Print)1860-949X

Fingerprint

Power quality
Artificial intelligence
Digital devices
Monitoring
Outages
Microprocessor chips
Signal processing
Productivity

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Hur, K., & Santoso, S. (2010). Power quality. In B. K. Panigrahi (Ed.), Computational Intelligence in Power Engineering (pp. 199-234). (Studies in Computational Intelligence; Vol. 302). https://doi.org/10.1007/978-3-642-14013-6_8
Hur, Kyeon ; Santoso, Surya. / Power quality. Computational Intelligence in Power Engineering. editor / Bijaya Ketan Panigrahi. 2010. pp. 199-234 (Studies in Computational Intelligence).
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Hur, K & Santoso, S 2010, Power quality. in BK Panigrahi (ed.), Computational Intelligence in Power Engineering. Studies in Computational Intelligence, vol. 302, pp. 199-234. https://doi.org/10.1007/978-3-642-14013-6_8

Power quality. / Hur, Kyeon; Santoso, Surya.

Computational Intelligence in Power Engineering. ed. / Bijaya Ketan Panigrahi. 2010. p. 199-234 (Studies in Computational Intelligence; Vol. 302).

Research output: Chapter in Book/Report/Conference proceedingChapter

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Hur K, Santoso S. Power quality. In Panigrahi BK, editor, Computational Intelligence in Power Engineering. 2010. p. 199-234. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-642-14013-6_8