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PV parameter identification using reduced I-V data

  • Shaun Tay
  • , Idris Lim
  • , Zhen Ye
  • , Dazhi Yang
  • , Ausias Garrigos
  • University of Glasgow
  • Elkem ASA
  • Agency for Science, Technology and Research, Singapore
  • Miguel Hernández University

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

Abstract

In this paper, possibility and accuracy of using reduced I-V data in PV parameter identification are discussed. Based on the linear identification method proposed in [1], six I-V points are used instead of the whole I-V curve to identify the PV parameters. The maximum power point (MPP) is then estimated using the identified I-V and P-V characteristics. Validation is done by using different sets of six points on the I-V curve. Experiment results show that the accurate curve fitting (with low RMSE and MPE) and good estimation of MPP can be achieved.

Original languageEnglish
Title of host publicationProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2653-2657
Number of pages5
ISBN (Electronic)9781538611272
DOIs
StatePublished - 15 Dec 2017
Externally publishedYes
Event43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China
Duration: 29 Oct 20171 Nov 2017

Publication series

NameProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Volume2017-January

Conference

Conference43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Country/TerritoryChina
CityBeijing
Period29/10/171/11/17

Keywords

  • I-V characteristics
  • Linear identification
  • Maximum power point estimation

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