Efficient Analytical Models for Accurate Peak Power Forecasting of Photovoltaic Panels under Real-World Conditions

A novel method has been devised to accurately predict the peak power output of photovoltaic panels under various real-world conditions, encompassing fluctuations in solar irradiation and module temperature from sunrise to sunset. This approach employs an explicit model with three pivotal parameters: the short-circuit current, the open-circuit voltage, and the shape parameter. This study introduces fresh models for the maximum power point, shape parameter, and the open-circuit voltage. Our predictive method is divided into two steps: firstly, parameter coefficients are extracted using measured data collected on a reference day, and subsequently, these parameters are forecasted under different conditions using only solar irradiance and back surface module temperature. Three distinct solar module technologies, namely monocrystalline, multi-crystalline, and amorphous silicon, are tested in Cocoa, Florida, and data are collected by the NREL laboratory. The normalized error indicator of predicted maximum output values for each of the three solar panels on June 21st, 2011, March 16th, 2011, and November 21st, 2011, remains within 2.7%, showcasing the accuracy and consistency of the proposed approach.