Unknown parameter estimation of a detailed solar PV cell model

Duy C. Huynh, Loc D. Ho, Matthew Walter Dunnigan

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

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Abstract

This paper proposes a novel technique for unknown parameter estimation of a detailed solar photovoltaic (PV) cell model based on the artificial bee colony (ABC) algorithm and particle swarm optimization (PSO) algorithm. This combination allows to balance between the exploration and exploitation abilities of each algorithm for achieving a good optimization performance. The detailed solar PV cell model is the double-diode model with seven unknown parameters which are estimated by using the hybrid ABC-PSO algorithm. The numerical results of the parameter estimation using the hybrid ABC-PSO algorithm are compared with those using the PSO, advanced PSO and ABC algorithms showing that the convergence speed and value of the hybrid ABC-PSO algorithm are always better than the PSO, advanced PSO and ABC algorithms.
Original languageEnglish
Title of host publication2020 IEEE Region 10 Conference (TENCON)
PublisherIEEE
Pages512-516
Number of pages5
ISBN (Electronic)9781728184555
DOIs
Publication statusPublished - 22 Dec 2020
Event2020 IEEE Region 10 Conference - Online, Osaka, Japan
Duration: 16 Nov 202019 Nov 2020

Conference

Conference2020 IEEE Region 10 Conference
Abbreviated titleTENCON 2020
Country/TerritoryJapan
CityOsaka
Period16/11/2019/11/20

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