Modeling I-V curves of photovoltaic modules at indoor and outdoor conditions by using the Lambert function

•Diode equivalent equation is solved by using the Lambert-W function.•I-V curves can be computed fast and accurately for every PV technology.•The methodology is quite sensitive to the input parameters uncertainty.•Well-controlled indoors temperature and irradiance proved the robustness. Accurate and...

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Bibliographic Details
Published in:Energy conversion and management 2019-09, Vol.195, p.1004-1011
Main Authors: Polo, Jesús, Martín-Chivelet, Nuria, Alonso-García, M. Carmen, Zitouni, Houssain, Alonso-Abella, Miguel, Sanz-Saiz, Carlos, Vela-Barrionuevo, Nieves
Format: Article
Language:English
Subjects:
I-V curve
Indoor and outdoor conditions
Iterative methods
Mathematical models
Modelling
Modules
Parameter uncertainty
Performance prediction
Photovoltaic cells
Photovoltaics
PV modeling
Sensitivity analysis
Solar cells
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Summary:•Diode equivalent equation is solved by using the Lambert-W function.•I-V curves can be computed fast and accurately for every PV technology.•The methodology is quite sensitive to the input parameters uncertainty.•Well-controlled indoors temperature and irradiance proved the robustness. Accurate and robust modeling of the characteristic I-V curve of a photovoltaic module is essential in many applications focused on forecasting and predicting photovoltaic (PV) performance. The single diode equivalent model has been used extensively for representing the working principles of solar cells. This work presents a simple methodology for solving the single diode equation from the manufacture’s datasheet parameters, by combining the Lambert-W function and an iterative procedure on the ideality factor of the diode, which has a fast convergence and robustness. The model has been assessed by comparing with experimental I-V curves measured for different modules at indoor and outdoor conditions with good results. Sensitivity analysis has been also done to indicate the possible impact of the uncertainty of the initial parameters that input the model.
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2019.05.085