Only few manufactures provide the wide set of graphical data that are necessary to use high performance predictive tools for PV systems. On the other hand, reliable graphical data require accurate laboratory measurements that increase manufacturing costs. For this reason PV system designers have to choose between the use of cheap PV modules, lacking in technical data, and the reliable energy predictions that are possible only if the current–voltage characteristics are provided by the PV module manufacturers. This paper describes the procedure to evaluate the parameters of a one-diode equivalent circuit able to accurately epresent the electrical behaviour of a PV panel by means of the minimum set of technical data that are usually provided by all manufacturers. To reach the purpose some correlations based on the survey of more than one hundred PV module characteristics were defined to make up for the lack of technical information. The computer routines used to evaluate the values of the model parameters are listed; the routines are written in BASIC and can be easily implemented, even like VBA macros in Microsoft Excel. The capability of the new model to calculate the current–voltage characteristics was tested by comparing the results with data measured by four different manufacturers. The results of the application of the new model confirm the reliability of the proposed procedure. The differences between the calculated and the measured data are always less than the data tolerance usually declared by the manufacturers.

Orioli, A., Di Gangi, A. (2014). Corrigendum to ‘‘A procedure to calculate the five-parameter model of crystalline silicon photovoltaic modules on the basis of the tabular performance data’’ [Appl. Energy 102 (2013) 1160–1177]. APPLIED ENERGY, 119(119), 566-566 [10.1016/j.apenergy.2012.06.036].

Corrigendum to ‘‘A procedure to calculate the five-parameter model of crystalline silicon photovoltaic modules on the basis of the tabular performance data’’ [Appl. Energy 102 (2013) 1160–1177]

ORIOLI, Aldo;DI GANGI, Alessandra
2014-01-01

Abstract

Only few manufactures provide the wide set of graphical data that are necessary to use high performance predictive tools for PV systems. On the other hand, reliable graphical data require accurate laboratory measurements that increase manufacturing costs. For this reason PV system designers have to choose between the use of cheap PV modules, lacking in technical data, and the reliable energy predictions that are possible only if the current–voltage characteristics are provided by the PV module manufacturers. This paper describes the procedure to evaluate the parameters of a one-diode equivalent circuit able to accurately epresent the electrical behaviour of a PV panel by means of the minimum set of technical data that are usually provided by all manufacturers. To reach the purpose some correlations based on the survey of more than one hundred PV module characteristics were defined to make up for the lack of technical information. The computer routines used to evaluate the values of the model parameters are listed; the routines are written in BASIC and can be easily implemented, even like VBA macros in Microsoft Excel. The capability of the new model to calculate the current–voltage characteristics was tested by comparing the results with data measured by four different manufacturers. The results of the application of the new model confirm the reliability of the proposed procedure. The differences between the calculated and the measured data are always less than the data tolerance usually declared by the manufacturers.
2014
Settore ING-IND/11 - Fisica Tecnica Ambientale
Orioli, A., Di Gangi, A. (2014). Corrigendum to ‘‘A procedure to calculate the five-parameter model of crystalline silicon photovoltaic modules on the basis of the tabular performance data’’ [Appl. Energy 102 (2013) 1160–1177]. APPLIED ENERGY, 119(119), 566-566 [10.1016/j.apenergy.2012.06.036].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/98030
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