Leveraging MPPT capability for solar irradiance estimation: H-INC-IBS-based assessment of explicit models under real-world climatic conditions

Abstract

This research investigates a low-cost method for estimating irradiance. The approach uses maximum power point tracking (MPPT) to easily estimate irradiance in a Photovoltaic (PV) system. Two main explicit mathematical models "IV-G" and "I-G" are examined for effective irradiance estimation. Given the requirement for MPPT, the examined PV system is powered by a hybrid-incremental conductance integral backstepping controller (H-INC-IBS), which enables proper maximum power point functioning. These models are evaluated using statistical indices such as the root mean square error (RMSE), mean absolute percentage error (MAPE), symmetrical mean absolute percentage error (SMAPE), and coefficient of correlation (R). The research tests these models using 37 climate patterns, demonstrating the influence of MPPT on model performance. In addition, the models are closely monitored in an experimental setup that includes two consecutive days of real-time climatic exposure. The experimental results show that the I-G model has the best accuracy measures, with worst MAE, MAPE, and SMAPE values of 18.81 W, 8.9039 %, and 4.7242 %, respectively. Thus, the article concludes that the I-G model is better suited for irradiance estimate in the context of MPPT. Furthermore, using evidence-based study outcomes, the paper proves that MPPT accuracy is proportional to estimating model accuracy. Given the little attention paid to this area of irradiance estimation, this work is intended to serve as a reference in the field.