Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting

Authors

  • Valdemar M. Cavalcante Junior Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil https://orcid.org/0009-0000-3859-1182
  • Tiago A. Fernandes Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil. https://orcid.org/0009-0008-1600-2955
  • Renato Andrade Freitas Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil. https://orcid.org/0009-0007-4062-4853
  • Nayara A. de M. S. Amâncio Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil. https://orcid.org/0009-0004-5040-0683
  • Fabricio Bradaschia Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil. https://orcid.org/0000-0002-2086-7862
  • Marcelo Cabral Cavalcanti Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil. https://orcid.org/0000-0003-0157-0841

DOI:

https://doi.org/10.18618/REP.2005.1.063070

Keywords:

Energy Production, GNLM, NMAEP, Optimization Algorithms, Photovoltaic

Abstract

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.

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Author Biographies

Valdemar M. Cavalcante Junior, Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil

born in 1994 in Garanhuns, is a control and automation engineer (2020) and holds a master's degree in electrical engineering (2023) from the Federal University of Pernambuco. His main research interests include photovoltaic module modeling, power electronics and renewable energy systems. MSc. Valdemar M. Cavalcante Junior is a student member of the SOBRAEP and IEEE.

Tiago A. Fernandes, Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil.

born in 2000 in Recife, is an undergraduate student in Electrical Engineering (2018) at the Federal University of Pernambuco. His main research interests include modeling of photovoltaic modules, power electronics, and renewable energy systems. Tiago A. Fernandes is a student member of the SOBRAEP.

Renato Andrade Freitas, Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil.

born in 1988 in Aracaju, is electrical engineering (2012) at the Federal University of Campina Grande. His main research interests include modeling of photovoltaic modules, power electronics, and renewable energy systems. Renato Andrade Freitas is a student member of the SOBRAEP and IEEE.

Nayara A. de M. S. Amâncio, Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil.

born in 2000 in Jaboatão dos Guararapes, is an undergraduate student in Electrical Engineering (2019) at the Federal University of Pernambuco. His main research interests include modeling of photovoltaic modules, power electronics, and renewable energy systems.

Fabricio Bradaschia, Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil.

born in 1983 in São Paulo, is an electrical engineer (2006), Master (2008) and PhD in Electrical Engineering (2012) from the Federal University of Pernambuco. From August 2008 to August 2009, he worked as a visiting scholar at the University of Alcalá, Madrid, Spain. Since October 2013, he has been working as an adjunct professor in the Department of Electrical Engineering at the Federal University of Pernambuco. His research interests are the application of power electronics in photovoltaic systems and power quality, including pulse width modulation, converter topologies and network synchronization methods. Dr. Fabricio Bradaschia is a member of the SOBRAEP.

Marcelo Cabral Cavalcanti, Center for Technology and Geosciences, Department of Electrical Engineering, Federal University of Pernambuco, Recife - PE, 50740-550, Brazil.

born in 1972 in Recife, is an electrical engineer (1997) from the Federal University of Pernambuco, Master (1999) and PhD in Electrical Engineering (2003) from the Federal University of Campina Grande. He did a sandwich doctorate at the Center for Power Electronics Systems, Virginia Tech, USA between October 2001 and August 2002. Since 2005, he has been a professor in the Electrical Engineering Department at UFPE, where he is now a full professor. He did a Post-Doctorate at the Universidad de Alcalá, Spain between September 2012 and August 2013. His research interests are the application of power electronics in photovoltaic systems and power quality, including pulse width modulation and converter topologies. Dr. Marcelo C. Cavalcanti is a member of SOBRAEP's deliberative council. From 2016 to 2017 he was editor of SOBRAEP's Power Electronics magazine and from 2018 to 2019 he was president of SOBRAEP.

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Published

2024-06-24

How to Cite

[1]
V. M. Cavalcante Junior, T. A. Fernandes, R. A. Freitas, N. A. de M. S. Amâncio, F. Bradaschia, and M. C. Cavalcanti, “Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting”, Eletrônica de Potência, vol. 29, p. e202414, Jun. 2024.

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