LAPSE:2024.1611
Published Article

LAPSE:2024.1611
Optimal Transition of Ammonia Supply Chain Networks via Stochastic Programming
August 16, 2024. Originally submitted on July 9, 2024
Abstract
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.
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.
Record ID
Keywords
Capacity Expansion, Design and Sustainability, Green Ammonia, Stochastic Optimization, Supply Chain Optimization
Subject
Suggested Citation
Mitrai I, Palys MJ, Daoutidis P. Optimal Transition of Ammonia Supply Chain Networks via Stochastic Programming. Systems and Control Transactions 3:807-813 (2024) https://doi.org/10.69997/sct.141495
Author Affiliations
Mitrai I: University of Minnesota, Department of Chemical Engineering and Materials Science, Minneapolis, 55455 MN, US
Palys MJ: University of Minnesota, Department of Chemical Engineering and Materials Science, Minneapolis, 55455 MN, US
Daoutidis P: University of Minnesota, Department of Chemical Engineering and Materials Science, Minneapolis, 55455 MN, US
Palys MJ: University of Minnesota, Department of Chemical Engineering and Materials Science, Minneapolis, 55455 MN, US
Daoutidis P: University of Minnesota, Department of Chemical Engineering and Materials Science, Minneapolis, 55455 MN, US
Journal Name
Systems and Control Transactions
Volume
3
First Page
807
Last Page
813
Year
2024
Publication Date
2024-07-10
Version Comments
DOI Assigned
Other Meta
PII: 0807-0813-676183-SCT-3-2024, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2024.1611
This Record
External Link

https://doi.org/10.69997/sct.141495
Article DOI
Download
Meta
Links to Related Works