Improved Quality Parameter Estimation of Photovoltaic System Models based on SAO Algorithm

Rim Attafi; Naoufal Zitouni; Masoud Dashtdar; Aymen Flah; Mohamed F. Elnaggar; Mohammad Kanan

doi:10.48084/etasr.7919

Improved Quality Parameter Estimation of Photovoltaic System Models based on SAO Algorithm

Rim Attafi, Naoufal Zitouni, Masoud Dashtdar, Aymen Flah, Mohamed F. Elnaggar, Mohammad Kanan

Electrical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Solar energy provides one of the most favorable options regarding the transition to clean energy sources. The parameters of a photovoltaic (PV) system play determine its performance under various scenarios. The PV model parameter estimation is an example of nonlinear planning. This study proposes a novel use of the established Smell Agent Optimizer (SAO) algorithm to anticipate the undefined parameters of the PV model's single-diode and two-diode equivalent circuits. This study aims to create a precise PV model that can accurately characterize its performance under changing operational conditions. The desired objective function is defined as the square of the mean squared error between the model's current-voltage curve and the measured curve.

Original language	English
Pages (from-to)	15882-15887
Number of pages	6
Journal	Engineering, Technology and Applied Science Research
Volume	14
Issue number	4
DOIs	https://doi.org/10.48084/etasr.7919
State	Published - Aug 2024

Keywords

parameter identification
Photovoltaic systems
SAO algorithm

UN SDGs

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

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10.48084/etasr.7919

Cite this

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title = "Improved Quality Parameter Estimation of Photovoltaic System Models based on SAO Algorithm",

abstract = "Solar energy provides one of the most favorable options regarding the transition to clean energy sources. The parameters of a photovoltaic (PV) system play determine its performance under various scenarios. The PV model parameter estimation is an example of nonlinear planning. This study proposes a novel use of the established Smell Agent Optimizer (SAO) algorithm to anticipate the undefined parameters of the PV model's single-diode and two-diode equivalent circuits. This study aims to create a precise PV model that can accurately characterize its performance under changing operational conditions. The desired objective function is defined as the square of the mean squared error between the model's current-voltage curve and the measured curve.",

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AU - Attafi, Rim

AU - Zitouni, Naoufal

AU - Dashtdar, Masoud

AU - Flah, Aymen

AU - Elnaggar, Mohamed F.

AU - Kanan, Mohammad

N1 - Publisher Copyright: © by the authors.

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N2 - Solar energy provides one of the most favorable options regarding the transition to clean energy sources. The parameters of a photovoltaic (PV) system play determine its performance under various scenarios. The PV model parameter estimation is an example of nonlinear planning. This study proposes a novel use of the established Smell Agent Optimizer (SAO) algorithm to anticipate the undefined parameters of the PV model's single-diode and two-diode equivalent circuits. This study aims to create a precise PV model that can accurately characterize its performance under changing operational conditions. The desired objective function is defined as the square of the mean squared error between the model's current-voltage curve and the measured curve.

AB - Solar energy provides one of the most favorable options regarding the transition to clean energy sources. The parameters of a photovoltaic (PV) system play determine its performance under various scenarios. The PV model parameter estimation is an example of nonlinear planning. This study proposes a novel use of the established Smell Agent Optimizer (SAO) algorithm to anticipate the undefined parameters of the PV model's single-diode and two-diode equivalent circuits. This study aims to create a precise PV model that can accurately characterize its performance under changing operational conditions. The desired objective function is defined as the square of the mean squared error between the model's current-voltage curve and the measured curve.

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KW - Photovoltaic systems

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Improved Quality Parameter Estimation of Photovoltaic System Models based on SAO Algorithm

Abstract

Keywords

UN SDGs

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