Dandelion Optimizer (DO) algorithm for Parameters Extraction of Photovoltaic Solar Cell

Recently, Renewable energy has become the hottest research topic for energy researchers. Due to environmental concerns over previous energy sources, solar energy is the most promising form of renewable energy source, which is being increasingly used. The accurate parameters of a solar photovoltaic (...

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Published in2023 1st International Conference on Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET) pp. 1 - 6
Main Authors Zahia, Djeblahi, Belkacem, Mahdad, Kamel, Srairi
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.05.2023
Subjects
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DOI10.1109/ICRSEtoSET56772.2023.10525575

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Abstract Recently, Renewable energy has become the hottest research topic for energy researchers. Due to environmental concerns over previous energy sources, solar energy is the most promising form of renewable energy source, which is being increasingly used. The accurate parameters of a solar photovoltaic (PV) system models have a significant impact on the efficiency with which solar energy is converted into electricity. The simulation and controlling of PV systems require the extraction of their unknown parameters. In this research work, a novel metaheuristic swarm-intelligence bio-inspired optimization algorithm, called the Dandelion Optimizer (DO) is utilized to extract the parameters for identifying continuous optimization problems in PV solar cell models. The efficacy of the proposed algorithm is evaluated against other well-known metaheuristic algorithms. The results demonstrate the superiority of the proposed method in extracting the PV parameters for both single and double-diode models.
AbstractList Recently, Renewable energy has become the hottest research topic for energy researchers. Due to environmental concerns over previous energy sources, solar energy is the most promising form of renewable energy source, which is being increasingly used. The accurate parameters of a solar photovoltaic (PV) system models have a significant impact on the efficiency with which solar energy is converted into electricity. The simulation and controlling of PV systems require the extraction of their unknown parameters. In this research work, a novel metaheuristic swarm-intelligence bio-inspired optimization algorithm, called the Dandelion Optimizer (DO) is utilized to extract the parameters for identifying continuous optimization problems in PV solar cell models. The efficacy of the proposed algorithm is evaluated against other well-known metaheuristic algorithms. The results demonstrate the superiority of the proposed method in extracting the PV parameters for both single and double-diode models.
Author Zahia, Djeblahi
Kamel, Srairi
Belkacem, Mahdad
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  organization: Biskra University,Department of Electrical Engineering,Biskra,Algeria
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Snippet Recently, Renewable energy has become the hottest research topic for energy researchers. Due to environmental concerns over previous energy sources, solar...
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SubjectTerms Biological system modeling
Dandelion Optimizer (DO)algorithm
double-diode model
Ecosystems
Electricity
metaheuristic algorithms
Metaheuristics
Parameter extraction
Photovoltaic cells
Photovoltaic solar cell
Photovoltaic systems
Renewable energy sources
single diode model
Title Dandelion Optimizer (DO) algorithm for Parameters Extraction of Photovoltaic Solar Cell
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