TY - JOUR
T1 - Tree Growth Based Optimization Algorithm for Parameter Extraction of Different Models of Photovoltaic Cells and Modules
AU - Diab, Ahmed A.Zaki
AU - Sultan, Hamdy M.
AU - Aljendy, Raseel
AU - Al-Sumaiti, Ameena Saad
AU - Shoyama, Masahito
AU - Ali, Ziad M.
N1 - Funding Information:
This work was supported by Khalifa University, Abu Dhabi, United Arab Emirates under Award FSU-2018-25.
Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - Among all renewable energy sources, solar cells are considered the most popular solution for a clean source of energy and have a wide range of applications from few watts to Megawatt industrial and domestic loads. Building a precise mathematical model based on nonlinear equations for solar cells as well as photovoltaic (PV) modules is an essential issue for reasonable performance assessment, control and optimal operation of PV energy systems. In the current study, a novel optimization algorithm, Tree Growth Algorithm (TGA), is applied for accurate and efficient extraction of the unknown solar cell and PV module parameters. TGA is applied for estimating the unidentified parameters of PV models. Single diode model (SDM), double diode model (DDM) and three diode model (TDM) are investigated in the mathematical models of both solar cells and PV modules. The obtained results from the application of TGA to achieve this objective are compared with different algorithms reported in the literature. Moreover, the results demonstrated that the proposed algorithm of TGA superior to other reported methods. The good matching of the I-V characteristic curve of the computed parameters with those of the measured data from the manufacturer's PV modules/cells datasheet proved that the proposed TGA may function as a competitor to the methods provided in literature for parameters' identification of PV of solar cells.
AB - Among all renewable energy sources, solar cells are considered the most popular solution for a clean source of energy and have a wide range of applications from few watts to Megawatt industrial and domestic loads. Building a precise mathematical model based on nonlinear equations for solar cells as well as photovoltaic (PV) modules is an essential issue for reasonable performance assessment, control and optimal operation of PV energy systems. In the current study, a novel optimization algorithm, Tree Growth Algorithm (TGA), is applied for accurate and efficient extraction of the unknown solar cell and PV module parameters. TGA is applied for estimating the unidentified parameters of PV models. Single diode model (SDM), double diode model (DDM) and three diode model (TDM) are investigated in the mathematical models of both solar cells and PV modules. The obtained results from the application of TGA to achieve this objective are compared with different algorithms reported in the literature. Moreover, the results demonstrated that the proposed algorithm of TGA superior to other reported methods. The good matching of the I-V characteristic curve of the computed parameters with those of the measured data from the manufacturer's PV modules/cells datasheet proved that the proposed TGA may function as a competitor to the methods provided in literature for parameters' identification of PV of solar cells.
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U2 - 10.1109/ACCESS.2020.3005236
DO - 10.1109/ACCESS.2020.3005236
M3 - Article
AN - SCOPUS:85088319761
SN - 2169-3536
VL - 8
SP - 119668
EP - 119687
JO - IEEE Access
JF - IEEE Access
M1 - 9126782
ER -
