Optimal Transition of Ammonia Supply Chain Networks via Stochastic Programming

This paper considers the optimal incorporation of renewable ammonia production facilities into existing supply chain networks which import ammonia from conventional producers while accounting for uncertainty in this conventional ammonia price. We model the supply chain transition problem as a two-stage stochastic optimization problem which is formulated as a Mixed Integer Linear Programming problem. We apply the proposed approach to a case study on Minnesota's ammonia supply chain. We find that accounting for conventional price uncertainty leads to earlier incorporation of in-state renewable production sites in the supply chain network and a reduction in the quantity and cost of conventional ammonia imported over the supply chain transition horizon. These results show that local renewable ammonia production can act as a hedge against the volatility of the conventional ammonia market.