A Two-Stage Stochastic Programming Approach for the Design of Renewable Ammonia Supply Chain Networks

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This work considers the incorporation of renewable ammonia manufacturing sites into existing ammonia supply chain networks while accounting for ammonia price uncertainty from existing producers. We propose a two-stage stochastic programming approach to determine the optimal investment decisions such that the ammonia demand is satisfied and the net present cost is minimized. We apply the proposed approach to a case study considering deploying in-state renewable ammonia manufacturing in Minnesota’s supply chain network. We find that accounting for price uncertainty leads to supply chains with more ammonia demand met via renewable production and thus lower costs from importing ammonia from existing producers. These results show that the in-state renewable production of ammonia can act as a hedge against the volatility of the conventional ammonia market.

Original languageEnglish (US)
Article number325
Issue number2
StatePublished - Feb 2024

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  • capacity expansion
  • green ammonia
  • stochastic optimization
  • supply chain optimization

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