Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting
The article explores the relevance of choosing the optimization algorithm to obtain accurate parameter estimates in photovoltaic (PV) systems, with the aim of improving the energy efficiency of solar energy. Advances in photovoltaic module analysis models have resulted in the development of global n...
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| Format: | Article |
| Language: | English |
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Associação Brasileira de Eletrônica de Potência
2024-06-01
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| Series: | Eletrônica de Potência |
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| Online Access: | https://journal.sobraep.org.br/index.php/rep/article/view/919 |
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| author | Valdemar M. Cavalcante Junior Tiago A. Fernandes Renato Andrade Freitas Nayara A. de M. S. Amâncio Fabricio Bradaschia Marcelo Cabral Cavalcanti |
| author_facet | Valdemar M. Cavalcante Junior Tiago A. Fernandes Renato Andrade Freitas Nayara A. de M. S. Amâncio Fabricio Bradaschia Marcelo Cabral Cavalcanti |
| author_sort | Valdemar M. Cavalcante Junior |
| collection | DOAJ |
| description | The article explores the relevance of choosing the optimization algorithm to obtain accurate parameter estimates in photovoltaic (PV) systems, with the aim of improving the energy efficiency of solar energy. Advances in photovoltaic module analysis models have resulted in the development of global non-linear models (GNLM), which offer a more accurate representation of the I-V characteristics under various environmental conditions. Metaheuristic algorithms have stood out for their ability to handle the complexity of these nonlinear models. Therefore, the careful choice of the optimization algorithm is fundamental to guarantee consistent and reliable results in the estimation of the model parameters, contributing to maximizing energy efficiency. The study seeks to investigate whether different optimization tools can improve the accuracy and efficiency of parameter estimation, resulting in improved modeling and performance prediction of PV systems in different conditions. |
| format | Article |
| id | doaj-art-ff12b22a749f45fd874a7d34dc1b3c7f |
| institution | OA Journals |
| issn | 1414-8862 1984-557X |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Associação Brasileira de Eletrônica de Potência |
| record_format | Article |
| series | Eletrônica de Potência |
| spelling | doaj-art-ff12b22a749f45fd874a7d34dc1b3c7f2025-08-20T01:47:50ZengAssociação Brasileira de Eletrônica de PotênciaEletrônica de Potência1414-88621984-557X2024-06-0129e202414e20241410.18618/REP.2005.1.063070919Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation ForecastingValdemar M. Cavalcante Junior0https://orcid.org/0009-0000-3859-1182Tiago A. Fernandes1https://orcid.org/0009-0008-1600-2955Renato Andrade Freitas2https://orcid.org/0009-0007-4062-4853Nayara A. de M. S. Amâncio3https://orcid.org/0009-0004-5040-0683Fabricio Bradaschia4https://orcid.org/0000-0002-2086-7862Marcelo Cabral Cavalcanti5https://orcid.org/0000-0003-0157-0841Universidade Federal de Pernambuco Universidade Federal de Pernambuco Universidade Federal de Pernambuco Universidade Federal de Pernambuco Universidade Federal de Pernambuco Universidade Federal de Pernambuco The article explores the relevance of choosing the optimization algorithm to obtain accurate parameter estimates in photovoltaic (PV) systems, with the aim of improving the energy efficiency of solar energy. Advances in photovoltaic module analysis models have resulted in the development of global non-linear models (GNLM), which offer a more accurate representation of the I-V characteristics under various environmental conditions. Metaheuristic algorithms have stood out for their ability to handle the complexity of these nonlinear models. Therefore, the careful choice of the optimization algorithm is fundamental to guarantee consistent and reliable results in the estimation of the model parameters, contributing to maximizing energy efficiency. The study seeks to investigate whether different optimization tools can improve the accuracy and efficiency of parameter estimation, resulting in improved modeling and performance prediction of PV systems in different conditions.https://journal.sobraep.org.br/index.php/rep/article/view/919energy productiongnlmnmaepoptimization algorithmsphotovoltaic |
| spellingShingle | Valdemar M. Cavalcante Junior Tiago A. Fernandes Renato Andrade Freitas Nayara A. de M. S. Amâncio Fabricio Bradaschia Marcelo Cabral Cavalcanti Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting Eletrônica de Potência energy production gnlm nmaep optimization algorithms photovoltaic |
| title | Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting |
| title_full | Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting |
| title_fullStr | Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting |
| title_full_unstemmed | Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting |
| title_short | Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting |
| title_sort | impact of optimization algorithm choice on nonlinear global model for photovoltaic energy generation forecasting |
| topic | energy production gnlm nmaep optimization algorithms photovoltaic |
| url | https://journal.sobraep.org.br/index.php/rep/article/view/919 |
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