Comparative Assessment of PV Power Models under Semiarid Conditions

The reliability of energy predictions for hot and semi-arid regions heavily depends on the accuracy of photovoltaic (PV) power modeling because system performance is influenced by environmental stressors. This paper uses a dataset validated by the manufacturer and representative of semi-arid operating conditions for the comparative analysis of four power modeling techniques for PV, empirical, semi-empirical, thermal, and hybrid. This dataset consists of cell temperatures ranging from ۱۵°C to ۶۵°C and irradiance values ranging from ۳۰۰ to ۱۰۰۰ W/m². To standardize and control for replicability, all models were executed and assessed within the same MATLAB environment. The hybrid semi-empirical model (Model ۳) is identified as the best-performing approach, as it remained consistent with a mean absolute relative error (MARE) of ۵% across all scenarios tested. Conversely, other thermal-based and empirical models were observed to exhibit significant biases under varying thermal and irradiance conditions. The advantages of hybrid models for predicting photovoltaic performance in data-limited climates are highlighted, providing system planners and designers with a framework.

کلیدواژه ها:

Photovoltaic modeling ، PV performance ، semi-arid climate ، Synthetic Dataset ، solar energy forecasting