Identification of Photovoltaic Array Model Parameters by Robust Linear Regression Methods

Authors

  • Maria Carmela Di Piazza Consiglio Nazionale delle Ricerche Istituto di Studi sui Sistemi Intelligenti per l’Automazione Author
  • Antonella Ragusa Consiglio Nazionale delle Ricerche Istituto di Studi sui Sistemi Intelligenti per l’Automazione Author
  • Gianpaolo Vitale Consiglio Nazionale delle Ricerche Istituto di Studi sui Sistemi Intelligenti per l’Automazione Author

DOI:

https://doi.org/10.24084/repqj07.268

Keywords:

Models and simulation of renewable energy sources, Photovoltaic array, Statistics

Abstract

The aim of this paper is to propose an approach for photovoltaic (PV) sources modeling based on robust least squares linear regression (LSR) parameter identification method. On the basis of experimental data of solar irradiance, cell temperature and voltage and currents at maximum power points for a given PV array, correlation functions among the considered quantities are defined. By implementing these functions in a Matlab® Simulink model, accurate I-V characteristics for the considered array are obtained, managing only the solar irradiance. The method is validated comparing the computed and the experimental maximum power points (MPPs). Its effectiveness is proven to be better with respect of parameter identification methods based on discrete approaches and standard LSR method

Published

2024-01-24

Issue

Section

Articles