Portada: Infraestructura para la Logística Sustentable 2050
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Infraestructura para el desarrollo que queremos 2026-2030

Elaborado por el Consejo de Políticas de Infraestructura (CPI), este documento constituye una hoja de ruta estratégica para orientar la inversión y la gestión de infraestructura en Chile. Presenta propuestas organizadas en siete ejes estratégicos, sin centrarse en proyectos específicos, sino en influir en las decisiones de política pública para promover una infraestructura que conecte territorios, genere oportunidades y eleve la calidad de vida de la población.
ARTÍCULO
TITULO

Modeling and Simulation of Photovoltaic Modules Using Bio-Inspired Algorithms

Lucas Lima Provensi    
Renata Mariane de Souza    
Gabriel Henrique Grala    
Rosângela Bergamasco    
Rafael Krummenauer and Cid Marcos Gonçalves Andrade    

Resumen

This research aims to employ and qualify the bio-inspired algorithms: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution Algorithm (DE) in the extraction of the parameters of the circuit equivalent to a photovoltaic module in the models of a diode and five parameters (1D5P) and two diodes and seven parameters (2D7P) in order to simulate the I-V characteristics curves for any irradiation and temperature scenarios. The peculiarity of this study stands in the exclusive use of information present in the module?s datasheet to carry out the full extraction and simulation process without depending on external sources of data or experimental data. To validate the methods, a comparison was made between the data obtained by the simulations with data from the module manufacturer in different scenarios of irradiation and temperature. The algorithm bound to the model with the highest accuracy was DE 1D5P, with a maximum relative error of 0.4% in conditions close to the reference and 3.61% for scenarios far from the reference. On the other hand, the algorithm that obtained the worst result in extracting parameters was the GA in the 2D7P model, which presented a maximum relative error of 9.59% in conditions far from the reference.

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