Investigating methods to improve photovoltaic thermal models at second-to-minute timescales

Abstract

This paper presents a range of methods to improve the accuracy of equation-based thermal models of PV modules at second-to-minute timescales. An RC-equivalent conceptual model for PV modules is presented, where wind effects are captured. A method is shown to determine the thermal time constant �� of PV modules from measured data and module material properties, and �� is subsequently used to make static thermal models dynamic by applying the Exponential Weighted Mean (EWM) approach to irradiance and wind signals. On average, �� is (6.3 & PLUSMN; 1.0) min for fixed-mount PV systems. Based on this conceptual model, the Filter-EWM-Mean Bias Error correction (FEM) methodology is developed. Two thermal models, WM1 and WM2, are proposed and compared against the models of Ross, Sandia, and Faiman on twenty-four datasets of fifteen sites, with time resolutions ranging from 1 s to 1 h, the majority of these at 1 min resolution. The FEM methodology is shown to reduce model errors (RMSE and MAE) on average for all sites and models versus the standard steady-state equivalent by -1.1 K and -0.75 K respectively.