Glaucio Pedro de Alcantara
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Glaucio Pedro de Alcantara has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Cid Marcos Gonçalves Andrade
Department of Chemical Engineering, State University of Maringá, Maringá 87020-900, Brazil
1 shared publication - Gabriel Henrique Grala
Department of Chemical Engineering, State University of Maringá, Maringá 87020-900, Brazil
1 shared publication - Lucas Lima Provensi
Department of Chemical Engineering, State University of Maringá, Maringá 87020-900, Brazil
1 shared publication - Oswaldo Curty da Motta Lima
Department of Chemical Engineering, State University of Maringá (UEM), Maringá 87020-900, PR, Brazil
1 shared publication - Rafael Krummenauer
Department of Mechanical Engineering, State University of Maring, Maring, Brazil
1 shared publication
Latest Publications
- Open Access
- 26 October 2023
- Published by MDPI AG in Inventions
- Vol. 8 (6) , 134
Investigation of the Use of Evolutionary Algorithms for Modeling and Simulation of Bifacial Photovoltaic Modules
The purpose of this study is to employ and improve evolutionary algorithms, namely the genetic algorithm (GA) and the differential evolution algorithm (DE), to extract the parameters of the equivalent circuit model (ECM) of a bifacial photovoltaic module using the representative model of a diode with five parameters (1D5P). The objective is to simulate the characteristics of the I–V curves for various irradiation and temperature scenarios. A distinctive feature of this study is the exclusive use of the information in the technical sheet of the bifacial module to conduct the entire extraction and simulation process, eliminating the need to resort to external sources of data or experimental data. To validate the methods, a comparison was made between the simulation results and the data provided by the bifacial module manufacturer, contemplating different scenarios of irradiation and temperature. The DE was the most accurate algorithm for the 1D5P model, which presented a maximum average error of 1.57%. In comparison, the GA presented a maximum average error of 1.98% in the most distant scenario of STC conditions. Despite the errors inherent to the simulations, none of the algorithms presented relative errors greater than 8%, which represents a satisfactory modeling for the different operational conditions of the bifacial photovoltaic modules.
- 26 October 2023
- Published by MDPI AG in Inventions
- Vol. 8 (6) , 134
Open AccessInvestigation of the Use of Evolutionary Algorithms for Modeling and Simulation of Bifacial Photovoltaic Modules
The purpose of this study is to employ and improve evolutionary algorithms, namely the genetic algorithm (GA) and the differential evolution algorithm (DE), to extract the parameters of the equivalent circuit model (ECM) of a bifacial photovoltaic module using the representative model of a diode with five parameters (1D5P). The objective is to simulate the characteristics of the I–V curves for various irradiation and temperature scenarios. A distinctive feature of this study is the exclusive use of the information in the technical sheet of the bifacial module to conduct the entire extraction and simulation process, eliminating the need to resort to external sources of data or experimental data. To validate the methods, a comparison was made between the simulation results and the data provided by the bifacial module manufacturer, contemplating different scenarios of irradiation and temperature. The DE was the most accurate algorithm for the 1D5P model, which presented a maximum average error of 1.57%. In comparison, the GA presented a maximum average error of 1.98% in the most distant scenario of STC conditions. Despite the errors inherent to the simulations, none of the algorithms presented relative errors greater than 8%, which represents a satisfactory modeling for the different operational conditions of the bifacial photovoltaic modules.