The dynamic of photovoltaic resources on its performance predictability, based on two new approaches

The manuscript is a digest, which puts forward findings from previous research papers, combined with new proposals. Approaches comprise two full models' derivation for photovoltaic (PV) systems energy conversion predictability. It brings in several models for key physical observables formulated as functions of the operating conditions. The proposals encompass mean spectral reflectance, coefficient for reflections and spatial geometry, incident angular losses factor, angular losses, and fill factor along with its coefficient of temperature. Applying the superposition principle, these models are integrated into two full approaches for performance predictability. The underlying physics description is mathematically consistent with experimental measurements of the physical observables involved, reported in other studies. To the authors' knowledge, these full models have been reported previously nowhere. Simulation results from the more inaccurate of two full models show good agreement of these findings with the experimental evidence, reported of its performance. The resulting key performance indicators (KPIs), after simulating a grid‐connected PV system located in Cuba, yield 1.61%, 13.10%, −1.61%, 2.02%, and 0.81 of MAE, MAPE, MBE, RMSE, and R2, respectively, which they confirm the model's good behavior. Approaches formulations, as functions of solar irradiance and module temperature, its derivations, applications, and model's simulation results are considered the main manuscript novelties. The manuscript is a digest, which puts forward findings in previous research papers, combined with two full models for PV systems energy conversion predictability. Several models for key physical observables formulated as functions of the operating conditions. The proposals encompass mean spectral reflectance, coefficient for reflections and spatial geometry, incident angular losses factor, angular losses, fill factor along with its coefficient of temperature. By applying the superposition principle, these models are integrated into two full approaches for performance predictability. Highlights A digest on spectral reflectance and angular losses new models are treated. Liaison between approaches for angular losses and spectral reflectance is proved. Fill factor and its temperature coefficient new formulae are derived. Two full energy conversion performance models are described.