Online voltage stability monitoring of distribution system using optimized Support Vector Machine

Akanksha Shukla, Kusum Verma, Rajesh Kumar

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

7 Citations (Scopus)

Abstract

Voltage stability monitoring plays a significant role in secure and reliable operation of modern power systems. In this paper, two methods, (i) Particle Swarm Optimization (PSO) based Support Vector Machine (PSO-SVM) and (ii) Genetic Algorithm (GA) based Support Vector Machine (GA-SVM) is proposed for online voltage stability monitoring of distribution system. The optimal values of SVM parameters are obtained using PSO and GA algorithms. Comparison between proposed PSO-SVM and GA-SVM model are investigated on IEEE 33-bus radial distribution system. The results show that the PSO-SVM model for online voltage stability monitoring is more precise than GA-SVM.

Original languageEnglish
Title of host publication2016 IEEE 6th International Conference on Power Systems, ICPS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509001286
DOIs
Publication statusPublished - 5 Oct 2016
Externally publishedYes
Event6th IEEE International Conference on Power Systems, ICPS 2016 - New Delhi, India
Duration: 4 Mar 20166 Mar 2016

Publication series

Name2016 IEEE 6th International Conference on Power Systems, ICPS 2016

Conference

Conference6th IEEE International Conference on Power Systems, ICPS 2016
Country/TerritoryIndia
CityNew Delhi
Period4/03/166/03/16

Keywords

  • Distribution system
  • Genetic algorithm
  • Machine learning
  • Particle swarm optimization
  • Support vector machine
  • Voltage stability

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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