A critical part of the bioenergy production process is the robust design of the supply chain network. This research proposes robust optimization programming models to design a supply chain network that generates electricity from renewable energy sources under demand uncertainty. The objective is to design a biomass supply chain network that maximizes the profit of a power plant. Given the uncertain electricity demand, a two-stage stochastic programming model is proposed. A hybrid of risk-neutral and risk-averse modeling frameworks is proposed to analyze the alternative biomass-to-bioenergy supply chain design scenarios. The mathematical model has been proven to be effective in justifying the supply chain design based on a case study of the biomass-to-bioenergy supply chain in Iran. The research findings show that the proposed stochastic programming approach outperforms the conventional optimization approaches in terms of solution robustness.