TY - JOUR
T1 - Photovoltaic parameter estimation using improved moth flame algorithms with local escape operators
AU - Qaraad, Mohammed
AU - Amjad, Souad
AU - Hussein, Nazar K.
AU - Badawy, Mahmoud
AU - Mirjalili, Seyedali
AU - Elhosseini, Mostafa A.
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/3
Y1 - 2023/3
N2 - Optimizing, regulating, and simulating photovoltaic systems are crucial for producing solar energy. The performance of PV systems is greatly affected by model parameters, which can be variable and not always easily accessible. As a result, finding these model parameters is a constant goal. Current-voltage data is needed to extract characteristics of solar modules and construct high-accuracy models for the modeling, control, and optimization of photovoltaic systems. This paper introduces an Improved Moth Flame algorithm with Local escape operators (IMFOL). The LEO technique improves the MFO algorithm's efficiency and the results' precision. Furthermore, the LEO mechanism enhances both the diversity of the population and the MFO's exploration efficiency. This keeps the exploration and exploitation rates in equilibrium. The IMFO achieved the lowest RMSE for a double diode module, 9.8252542E-04, while IMFOL and JADE had the best RMSE for a single diode module, 9.8602E-04. Additionally, IMFOL obtained 2,42521000E-03 for the Photowatt-PWP 201 model and 1,72981457E-03 for the STM6-40/36 model. The proposed method surpasses the state-of-the-art in terms of accuracy, reliability, and output. IMFOL is a reliable tool for evaluating solar cell and PV module data.
AB - Optimizing, regulating, and simulating photovoltaic systems are crucial for producing solar energy. The performance of PV systems is greatly affected by model parameters, which can be variable and not always easily accessible. As a result, finding these model parameters is a constant goal. Current-voltage data is needed to extract characteristics of solar modules and construct high-accuracy models for the modeling, control, and optimization of photovoltaic systems. This paper introduces an Improved Moth Flame algorithm with Local escape operators (IMFOL). The LEO technique improves the MFO algorithm's efficiency and the results' precision. Furthermore, the LEO mechanism enhances both the diversity of the population and the MFO's exploration efficiency. This keeps the exploration and exploitation rates in equilibrium. The IMFO achieved the lowest RMSE for a double diode module, 9.8252542E-04, while IMFOL and JADE had the best RMSE for a single diode module, 9.8602E-04. Additionally, IMFOL obtained 2,42521000E-03 for the Photowatt-PWP 201 model and 1,72981457E-03 for the STM6-40/36 model. The proposed method surpasses the state-of-the-art in terms of accuracy, reliability, and output. IMFOL is a reliable tool for evaluating solar cell and PV module data.
KW - Local escaping operator
KW - Moth-flame optimization
KW - Parameter estimation
KW - Photovoltaic models
UR - http://www.scopus.com/inward/record.url?scp=85146592319&partnerID=8YFLogxK
U2 - 10.1016/j.compeleceng.2023.108603
DO - 10.1016/j.compeleceng.2023.108603
M3 - Article
AN - SCOPUS:85146592319
SN - 0045-7906
VL - 106
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
M1 - 108603
ER -