A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells
Solar energy is used worldwide to alleviate the daily increasing demands for electric power. Photovoltaic (PV) cells, which are used to convert solar energy into electricity, can be represented as equivalent circuit models, in which a series of electrical parameters must be identified in order to de...
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| Format: | Article |
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MDPI AG
2017-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/10/7/1052 |
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| author | Arturo Valdivia-González Daniel Zaldívar Erik Cuevas Marco Pérez-Cisneros Fernando Fausto Adrián González |
| author_facet | Arturo Valdivia-González Daniel Zaldívar Erik Cuevas Marco Pérez-Cisneros Fernando Fausto Adrián González |
| author_sort | Arturo Valdivia-González |
| collection | DOAJ |
| description | Solar energy is used worldwide to alleviate the daily increasing demands for electric power. Photovoltaic (PV) cells, which are used to convert solar energy into electricity, can be represented as equivalent circuit models, in which a series of electrical parameters must be identified in order to determine their operating characteristics under different test conditions. Intelligent approaches, like those based in population-based optimization algorithms like Particle Swarm Optimization (PSO), Genetic Algorithms (GAs), and Simulated Annealing (SA), have been demonstrated to be powerful methods for the accurate identification of such parameters. Recently, chaos theory have been highlighted as a promising alternative to increase the performance of such approaches; as a result, several chaos-based optimization methods have been devised to solve many different and complex engineering problems. In this paper, the Chaotic Gravitational Search Algorithm (CGSA) is proposed to solve the problem of accurate PV cell parameter estimation. To prove the feasibility of the proposed approach, a series of comparative experiments against other similar parameters extraction methods were performed. As shown by our experimental results, our proposed approach outperforms all other methods compared in this work, and proves to be an excellent alternative to tackle the challenging problem of solar cell parameters identification. |
| first_indexed | 2024-04-11T10:58:26Z |
| format | Article |
| id | doaj.art-2c7fc05f40314140a52bc8b11d5df186 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T10:58:26Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2c7fc05f40314140a52bc8b11d5df1862022-12-22T04:28:41ZengMDPI AGEnergies1996-10732017-07-01107105210.3390/en10071052en10071052A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic CellsArturo Valdivia-González0Daniel Zaldívar1Erik Cuevas2Marco Pérez-Cisneros3Fernando Fausto4Adrián González5Departamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430 Guadalajara, MexicoDepartamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430 Guadalajara, MexicoDepartamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430 Guadalajara, MexicoDepartamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430 Guadalajara, MexicoDepartamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430 Guadalajara, MexicoDepartamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430 Guadalajara, MexicoSolar energy is used worldwide to alleviate the daily increasing demands for electric power. Photovoltaic (PV) cells, which are used to convert solar energy into electricity, can be represented as equivalent circuit models, in which a series of electrical parameters must be identified in order to determine their operating characteristics under different test conditions. Intelligent approaches, like those based in population-based optimization algorithms like Particle Swarm Optimization (PSO), Genetic Algorithms (GAs), and Simulated Annealing (SA), have been demonstrated to be powerful methods for the accurate identification of such parameters. Recently, chaos theory have been highlighted as a promising alternative to increase the performance of such approaches; as a result, several chaos-based optimization methods have been devised to solve many different and complex engineering problems. In this paper, the Chaotic Gravitational Search Algorithm (CGSA) is proposed to solve the problem of accurate PV cell parameter estimation. To prove the feasibility of the proposed approach, a series of comparative experiments against other similar parameters extraction methods were performed. As shown by our experimental results, our proposed approach outperforms all other methods compared in this work, and proves to be an excellent alternative to tackle the challenging problem of solar cell parameters identification.https://www.mdpi.com/1996-1073/10/7/1052solar cellparameters identificationchaotic gravitational search algorithmpopulation-based algorithm |
| spellingShingle | Arturo Valdivia-González Daniel Zaldívar Erik Cuevas Marco Pérez-Cisneros Fernando Fausto Adrián González A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells Energies solar cell parameters identification chaotic gravitational search algorithm population-based algorithm |
| title | A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells |
| title_full | A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells |
| title_fullStr | A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells |
| title_full_unstemmed | A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells |
| title_short | A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells |
| title_sort | chaos embedded gravitational search algorithm for the identification of electrical parameters of photovoltaic cells |
| topic | solar cell parameters identification chaotic gravitational search algorithm population-based algorithm |
| url | https://www.mdpi.com/1996-1073/10/7/1052 |
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