An adaptive modelling technique for parameters extraction of photovoltaic devices under varying sunlight and temperature conditions

Abstract The batteries used with standalone PV systems are very sensitive to the current-voltage charging. Thus, for choosing the right battery, a PV system designer needs to make an accurate estimate of the current and voltage outputs of the PV module under consideration. However, this task is challenging due to randomness in the field operating conditions. To achieve this goal, the PV module in this work has been represented by a well-known equivalent one-diode electrical circuit with five unknown PV parameters. Using multiple current-voltage curves at different operating conditions, the proposed methodology extracts the five unknown PV parameters against each current-voltage curve. Each PV parameter is then plotted independently, first against the varying sunlight and then against the varying temperature. Then introducing a novel concept of shift-factors, the proposed methodology couples the two independent plots of each PV parameter and helps predict the value of that PV parameter at any operating condition. Unlike other works from the literature, the variations of these five PV parameters by the proposed methodology have been shown to be in accordance with the PV device theory and the physical behavior of the PV devices. The proposed model has been validated against both the PV panel’s datasheet information and the experimental in-field data. With realistic values captured for each PV parameter by the proposed methodology, the validations show a significant increase in the prediction accuracy of the current-voltage output of the PV panel. It has also been shown how this methodology can be used to better understand the behavior of the PV system and aid in its preventive/corrective maintenance.