Probabilistic risk assessment for an optimal selection of voltage sag mitigation devices using stochastic estimation of voltage sags

Jong Hoon Han, Gilsoo Jang, Chang Hyun Park

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

Abstract

Power quality mitigation devices play an important role in lots of industrial segments. Although there were many devices available in the market, the selection of an appropriate device specially for voltage sags and interruptions mitigation has been a challenge in the utility and customer for several years. It usually depends on technical and economic characteristics of the device. Nevertheless, most mitigation method is selected by rule of thumb or empirical method. In this paper, the expected sag frequency for a sensitive load was predicted by stochastic analysis then the life cycle cost analysis for the probabilistic risk assesment of voltage sag mitigation method is performed. Although the economic evaluation of power quality mitigation devices can never be specific, the optimal selection of devices used to mitigate power quality disruptions can be more effectively analyzed by probabilistic risk assessment.

Original languageEnglish
Title of host publicationAPAP 2011 - Proceedings
Subtitle of host publication2011 International Conference on Advanced Power System Automation and Protection
Pages1943-1946
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Advanced Power System Automation and Protection, APAP 2011 - Beijing, China
Duration: 2011 Oct 162011 Oct 20

Publication series

NameAPAP 2011 - Proceedings: 2011 International Conference on Advanced Power System Automation and Protection
Volume3

Other

Other2011 International Conference on Advanced Power System Automation and Protection, APAP 2011
CountryChina
CityBeijing
Period11/10/1611/10/20

Keywords

  • Area of vulnerability
  • life cycle cost
  • mitigation
  • power quality
  • probabilistic analysis
  • voltage sags

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

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