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Título del libro: Proceedings Of The Xxii 2020 Ieee International Autumn Meeting On Power, Electronics And Computing (ropec 2020), Vol 4
Título del capítulo: Statistical Method for Single-Diode Model Parameters Extraction of a Photovoltaic Module

Autores UNAM:
CARLOS ALVAREZ MACIAS; MICHEL ALEJANDRO RIVERO CORONA;
Autores externos:

Idioma:

Año de publicación:
2020
Palabras clave:

Errors; Incident solar radiation; Mean square error; Photovoltaic cells; Coefficient of determination; Mathematical expressions; Mean absolute percentage error; Operating temperature; Parameters estimation; Root mean square errors; Statistical criterion; Temperature conditions; Diodes


Resumen:

In this work a modeling method for photovoltaic (PV) modules based on statistical analysis is presented. In this sense, the work deals with the determination of the parameters of the non-linear I-V equation, represented by the single-diode model. The parameters estimation of the PV model starts with experimental tests on PV panels under different irradiance and temperature conditions. A database is built with the parameters extracted from the family of experimental curves, where mathematical expressions, through linear regression analysis, are obtained to determine electrical variables of interest, such as: I-sc, V-oc, I-m, V-m and Pm which are dependent of irradiance and/or operating temperature. The parameters of the non-linear I-V equation given by the resistances R-sh, R-s and the ideality factor n, the analysis demonstrate that average values are representative; while the light-generated and diode-saturation currents depend on the incident irradiance. The capacity of the models was validated through the analysis of different statistical criteria, such as: the root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and the coefficient of determination (R-2). The results were accepted for applications where a high precision is not necessary, or for modeling and/or forecasting purposes.


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