  Power supply from renewable resources is on a global rise where it is
forecasted that renewable generation will surpass other types of generation in
a foreseeable future. Increased generation from renewable resources, mainly
solar and wind, exposes the power grid to more vulnerabilities, conceivably due
to their variable generation, thus highlighting the importance of accurate
forecasting methods. This paper proposes a two-stage day-ahead solar
forecasting method that breaks down the forecasting into linear and nonlinear
parts, determines subsequent forecasts, and accordingly, improves accuracy of
the obtained results. To further reduce the error resulted from nonstationarity
of the historical solar radiation data, a data processing approach, including
pre-process and post-process levels, is integrated with the proposed method.
Numerical simulations on three test days with different weather conditions
exhibit the effectiveness of the proposed two-stage model.
