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 in | 2023 1st International Conference on Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET) pp. 1 - 6 |
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| Main Authors | , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
06.05.2023
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| Subjects | |
| Online Access | Get full text |
| DOI | 10.1109/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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: Djeblahi surname: Zahia fullname: Zahia, Djeblahi email: zahia.djeblahi@univ-biskra.dz organization: Biskra University,Department of Electrical Engineering,Biskra,Algeria – sequence: 2 givenname: Mahdad surname: Belkacem fullname: Belkacem, Mahdad email: belkacem.mahdad@univ-biskra.dz organization: Biskra University,Department of Electrical Engineering,Biskra,Algeria – sequence: 3 givenname: Srairi surname: Kamel fullname: Kamel, Srairi email: k.srairi@univ-biskra.dz organization: Biskra University,Department of Electrical Engineering,Biskra,Algeria |
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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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