Optimisation of Solar Photovoltaic (PV) Parameters Using Meta-Heuristics

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4 Citations (Scopus)
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Abstract

This paper presents a critical analysis of the meta-heuristic techniques used in various researches on the optimisation of photovoltaic (PV) parameters, which involves the use of different algorithms in order to extract and improve these parameters from the Single Diode Model (SDM), Double Diode Model (DDM) and Three Diode Model (TDM) respectively. The modelling parameters such as the photon current, saturation current, the series and parallel resistances are investigated to understand the optimum value. It will also equate the results of datasheet values from PV manufactures with experiment values obtained from PV module measurements. The meta-heuristics techniques to be considered include Genetic Algorithm (GA), Particle Swarm Optimisation (PSO), Harmony Search (HS), Flower Pollination Algorithm (FPA), Simulated Annealing (SA), Teaching Learning Based Optimisation (TLBO), and other different hybrid solutions to optimize the convergence speed. Root Mean Square Error (RMSE) is used as a performance indicator of each meta-heuristic technique. These optimisation techniques are utilised in extracting the parameters of a 5W polycrystalline panel at Standard testing conditions. The results presented in this paper compared the performances of the mentioned meta-heuristics on the single, double and triple diode models respectively.
Original languageEnglish
Pages (from-to)3161-3169
Number of pages9
JournalMicrosystem Technologies
Volume27
Issue number8
Early online date28 Oct 2020
DOIs
Publication statusPublished - Aug 2021

Bibliographical note

The final publication is available at Springer via http://dx.doi.org/10.1007/s00542-020-05066-3

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Funder

Institute of Future Cities and Transport, Coventry University

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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