Very-short term modeling of global solar radiation and air temperature data using curve fitting methods

The development of renewable energy technologies is an inevitable requirement to cope with environmental, economic and political challenges. Solar energy is regarded as one of the most promising types among renewable energy sources. So, the characterization of solar parameters is a significant process in solar energy installations. In this paper, we use three different curve fitting methods called Fourier, sum of sines and smoothing spline in order to model global solar radiation and air temperature parameters at 10-min intervals over a month. In the stage of accuracy comparison, we computed the coefficient of determination (R
²
) and the root mean squared error (RMSE) for the mentioned methods. In consequence, the smoothing spline model leads to the best modeling results.