SEASONAL MODELING OF HOURLY SOLAR IRRADIATION SERIES

Increasing usage of solar energy and the integration of photovoltaic power plants into the grid demand accurate knowledge and forecasting of the solar energy resources. This paper reports on the seasonal autoregressive integrated moving average model (sARIMA) applied to the hourly solar irradiation data series. The standard sARIMA model, a new adaptive sARIMA model and a model based on multi-valued logic are compared in terms of forecasting accuracy. A simple procedure of including relevant information into sARIMA model is proposed, by expressing the model coefficients as linear functions of external predictors, such as various radiometric and meteorological quantities and quantifiers for the state of the sky. Global and diffuse solar irradiance measured on the Solar Platform of the West University of Timisoara in 2009 and 2010 are used for testing. The results show that the models performances depend on the stability of the radiative regime, and that only minimal improvement is obtained by using the adaptive method.