A Study of Landsman, Sepic and Zeta Converter by Particle Swarm Optimization Technique

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

16 Scopus citations

Abstract

To enhance the quality of power generation from photovoltaic system, an acceptable power converter selection becomes more essential. DC-DC converters available are vast in power conversion system. Neverthless they are different in circuit configuration and ripple reduction. According to the performance and its efficiency for photovoltaic system, the converters are choosed. In this paper landsman converter, sepic converter, zeta converters are represented to determine its performance and efficiency. A particle swarm optimization has been employed to determine its efficiency (E). Apart from comparison of three different converters it is necessary to prescribe the inequalities among converters.

Original languageEnglish
Title of host publication2020 6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1035-1038
Number of pages4
ISBN (Electronic)9781728151977
DOIs
StatePublished - Mar 2020
Externally publishedYes
Event6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020 - Coimbatore, India
Duration: 6 Mar 20207 Mar 2020

Publication series

Name2020 6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020

Conference

Conference6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020
Country/TerritoryIndia
CityCoimbatore
Period6/03/207/03/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Efficiency(E)
  • Landsman Converter
  • Photo-Voltaic(PV)
  • Singe Ended Primary Inductor converter (SEPIC)
  • Zeta converter

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Information Systems and Management
  • Control and Optimization

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