This paper proposes a method for parameter identification of a photovoltaic (PV) source dynamic model. The identification procedure is based on a suitable time-domain step response and on a least-squares regression-based data processing algorithm. The considered equivalent circuit models the PV source as seen at load terminals; it is composed of a four-parameter static model and a dynamic part, which includes a capacitor with a series resistance and an inductance. The identification technique determines all three dynamic parameters with a single measurement. The proposed approach allows the appropriate dynamic modeling of the PV source and its connection cables, obtaining a better accuracy with respect to other methods in the technical literature. A practical case of parameter identification is presented.

Dynamic PV Model Parameter Identification by Least-Squares Regression

Maria Carmela Di Piazza;Massimiliano Luna;Gianpaolo Vitale
2013-01-01

Abstract

This paper proposes a method for parameter identification of a photovoltaic (PV) source dynamic model. The identification procedure is based on a suitable time-domain step response and on a least-squares regression-based data processing algorithm. The considered equivalent circuit models the PV source as seen at load terminals; it is composed of a four-parameter static model and a dynamic part, which includes a capacitor with a series resistance and an inductance. The identification technique determines all three dynamic parameters with a single measurement. The proposed approach allows the appropriate dynamic modeling of the PV source and its connection cables, obtaining a better accuracy with respect to other methods in the technical literature. A practical case of parameter identification is presented.
2013
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Least-squares regression (LSR)
modeling
photovoltaic (PV) source
simulation
statistics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/177974
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