Power quality assessment using a robust nonlinear estimation technique

V. V. Terzija, S. Wehrmann, V. Stanojevic, H. J. Koglin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes a new two stage robust Newton Type numerical algorithm for power quality assessment in electric power systems. In order to estimate current and voltage spectra simultaneously with the fundamental frequency, in the first algorithm stage, the robust Newton Type Algorithm is applied, in the second algorithm stage power quality indicators are calculated. Particularly the active, reactive, apparent and distortion powers are determined. As the main advantage, the technique provides estimates not sensitive to frequency deviations and bad data often appearing as a consequence of the communication error, incomplete measurement, errors in mathematical models etc. The algorithm performance is tested under laboratory conditions using the distorted voltage and current signals digitized during an AC-motor start.

Original languageEnglish
Title of host publication10th International Conference on Harmonics and Quality of Power, ICHQP 2002 - Proceedings
PublisherIEEE Computer Society
Pages155-161
Number of pages7
ISBN (Electronic)0780376714
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event10th International Conference on Harmonics and Quality of Power, ICHQP 2002 - Rio de Janeiro, Brazil
Duration: 6 Oct 20029 Oct 2002

Publication series

NameProceedings of International Conference on Harmonics and Quality of Power, ICHQP
Volume1
ISSN (Print)1540-6008
ISSN (Electronic)2164-0610

Conference

Conference10th International Conference on Harmonics and Quality of Power, ICHQP 2002
Country/TerritoryBrazil
CityRio de Janeiro
Period6/10/029/10/02

Keywords

  • Bad data
  • Laboratory and field-testing
  • Nonlinear robust estimation
  • Power measurement
  • Power quality

Fingerprint

Dive into the research topics of 'Power quality assessment using a robust nonlinear estimation technique'. Together they form a unique fingerprint.

Cite this