There is a growing interest in the use of biomass as a source of energy around the world. In the United States, the Renewable Fuel Standard (RFS) sets policies and mandates to support the production and consumption of biofuels. However, the uncertainties associated with the governmental and local policies and regulations on both production and consumption have imposed significant impacts on the biofuel supply chain network. This study aims to determine the optimal design of the biofuel supply chain to maximize annual profit under the impacts of governmental policies. In this study, two-stage stochastic programming models are developed in which conditional value at risk is considered as a risk measure to control the shortage of mandate. A case study in Iowa is conducted to investigate the effects of different policies and demonstrate the applicability and efficiency of the models.