Although it has been well recognized that clouds tremendously affect the surface solar irradiance and its direct and diffuse partitions, accurately forecasting solar radiation in cloudy conditions remains a major challenge. This study focuses on two aspects of the challenge: impacts of cloud microphysics and model domain size. First, we will examine the sensitivity of surface solar radiation and its partitions to cloud microphysics by using the state of art Weather Research and Forecasting model specifically designed for simulating and forecasting solar radiation (WRF-Solar). A number of microphysical schemes will be tested, and comparison against the measurements of shallow cumulus clouds and stratiform clouds selected at the DOE ARM SGP Site. Efforts will be made to quantify the resultant uncertainty spread. Second, identifying the physical causes of the underlying model differences is even more challenging. To address this, we will introduce a new model evaluation framework based on different setups of WRF-Solar (single column, LES, and nested WRF). In particular, we will examine the effect of the number of LES grid columns and its lower limit producing reasonable results. Commonly used evaluation metrics will be used in our model evaluation, including the used RMSE, MAE, MAPE, and relative Euclidean distance. The results will provide physical insight into the understanding of cloud-radiation interactions and forecasting of solar radiation in cloudy conditions.