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.
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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
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