Environmental concerns and the need for renewable resources in energy production increase the interest of researchers in the subject of the biomass supply chain. The widespread use of biomass requires the need for design and optimization of the biomass supply chain network for real-life conditions. The complex and largescale nature of the biomass supply chain leads to the existence of uncertainties that introduce several disruptions. Ignoring disruptions in the decision-making process makes the network design sensitive and vulnerable. The concept of resilient network design gives the biomass supply chain the ability to quickly adapt under changing conditions and maintain flow in cases of disruption. This study aims to develop a resilient biogas supply chain network design considering disruptive risks. A scenario-based mixed-integer linear programming model is developed under disruptions. Against both supply disruptions and facility disruptions, three resilience strategies are implemented: (1) multi-sourcing, (2) coverage distance, and (3) backup assignment strategy. To analyze and validate the effects of each proposed resilience strategy, comparative analyses are conducted considering several cases with different assumptions. For comparative analyses, the developed scenario-based optimization model is applied in the form of different model adjustments that incorporate the proposed resilience strategies. The applicability of the proposed resilience strategies is validated by analyzing their impact on the network structure, efficiency, production outputs, and economic performance of the supply chain. The impact of resilience strategies is reported and analyzed to make better inferences and contribute to managerial insights. Comparative results highlight that resilience strategies lead to improvement in different performance measures of the supply chain.