Application of Evolutionary Algorithms on Solar Photovoltaic System

Chitta Saha; Ammar Al Bazi

doi:10.1063/9780735424999_008

Application of Evolutionary Algorithms on Solar Photovoltaic System

Chitta Saha
, Ammar Al Bazi

College of Engineering, Environment & Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

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 language	English
Title of host publication	Artificial Intelligence for Smart Photovoltaic Technologies
Editors	Jingzheng Ren , Yi Man
Chapter	8
Pages	1-30
Number of pages	30
Edition	1
DOIs	https://doi.org/10.1063/9780735424999_008
Publication status	Published - 1 Jul 2022

Publication series

Name	Artificial Intelligence for Smart Photovoltaic Technologies
Publisher	AIP Publishing

UN SDGs

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

SDG 7 Affordable and Clean Energy

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10.1063/9780735424999_008

Cite this

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abstract = "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.",

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AB - 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.

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M3 - Chapter

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A2 - Ren , Jingzheng

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ER -

Application of Evolutionary Algorithms on Solar Photovoltaic System

Abstract

Publication series

UN SDGs

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