TY - CHAP
T1 - Application of Evolutionary Algorithms on Solar Photovoltaic System
AU - Saha, Chitta
AU - Al-Bazi, Ammar
N1 - Copyright © 2022 AIP Publishing LLC
PY - 2022/7
Y1 - 2022/7
N2 - 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.
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.
U2 - https://doi.org/10.1063/9780735424999_008
DO - https://doi.org/10.1063/9780735424999_008
M3 - Chapter (peer-reviewed)
SN - 9780735424999
T3 - Artificial Intelligence for Smart Photovoltaic Technologies
SP - 1
BT - Artificial Intelligence for Smart Photovoltaic Technologies
A2 - Ren, Jingzheng
A2 - Man, Yi
ER -