Application of Evolutionary Algorithms on Solar Photovoltaic System

Chitta Saha, Ammar Al-Bazi

Research output: Chapter in Book/Published conference outputChapter (peer-reviewed)peer-review


This book chapter begins with an overview of three equivalent circuit models of solar PV such as single diode model (SDM), double diode model (DDM) and three diode model (TDM), as well as critical comparison and analysis of each model. In addition, the extraction and optimisation of the solar PV parameters using various Evolutionary algorithms are discussed in this chapter. The modelling parameters such as the photon current, saturation current, the series and parallel resistances are investigated to understand the optimum value. It will compare the results of datasheet values from PV manufacturers with experimental values obtained from PV module measurements. Furthermore, the meta-heuristics techniques include genetic algorithm (GA), particle swarm optimisation (PSO), harmony search (HS), flower pollination algorithm (FPA), simulated annealing (SA), teaching learning-based optimisation (TLBO), and others will also be investigated.
Original languageEnglish
Title of host publicationArtificial Intelligence for Smart Photovoltaic Technologies
EditorsJingzheng Ren, Yi Man
Number of pages30
Publication statusPublished - Jul 2022

Publication series

Name Artificial Intelligence for Smart Photovoltaic Technologies
PublisherAIP Publishing

Bibliographical note

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