Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/11000/34238

Efficient computation of the photovoltaic single-diode model curve by means of a piecewise linear self-adaptive representation


Vista previa

Ver/Abrir:
 Toledo_etAl_2024_J. Comput. Sci._75_102199.pdf

1,77 MB
Adobe PDF
Compartir:
Título :
Efficient computation of the photovoltaic single-diode model curve by means of a piecewise linear self-adaptive representation
Autor :
Toledo Melero, Fco. Javier  
Galiano, Vicente  
Herranz Cuadrado, Maria Victoria  
Blanes, José M.
Editor :
Elsevier
Departamento:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Fecha de publicación:
2023
URI :
https://hdl.handle.net/11000/34238
Resumen :
The current–voltage curve (I–V curve) associated to the photovoltaic (PV) single-diode model (SDM) is an important tool to analyze the behavior of a PV panel, nevertheless, obtaining it is not easy due to the implicit nature of the SDM equation that requires a lot of computation to solve it accurately. In this paper we provide a simple, accurate and almost instantaneous method to obtain the I–V curve which can be easily programmed, for example, in a microcontroller. The main tool is a recent parametrization of the SDM I–V curve which allows to compute the I–V points explicitly when the slope of the curve is known. Then, an iterative sequence of points based in the mean slope between the points of the previous step is constructed. The new methodology is compared with the most common method and the superiority of our proposal is demonstrated with a large repository of curves. Moreover, using the distribution of points obtained with the new methodology, it is possible to represent, with high precision and speed, other curves such as the power and the curvature functions providing a deeper information of the SDM.
Palabras clave/Materias:
Piecewise linear interpolation
Photovoltaic single-diode model
Data point selection
Mean slope point
Graphical representation of functions
Data reduction
Área de conocimiento :
CDU: Ciencias puras y naturales: Matemáticas
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.1016/j.jocs.2023.102199
Aparece en las colecciones:
Artículos Estadística, Matemáticas e Informática



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.