Efthymiadou, Margarita E;
Charitopoulos, Vassilis M;
Papageorgiou, Lazaros G;
(2025)
Optimization Approach for Hydrogen Infrastructure Planning Under Uncertainty.
Industrial & Engineering Chemistry Research
, 64
(14)
pp. 7431-7451.
10.1021/acs.iecr.4c04211.
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Abstract
Toward the Net-Zero goal, deciphering trade-offs in strategic decisions for the role of hydrogen is vital for transitioning to low-carbon energy systems. This work proposes a two-stage stochastic optimization framework to provide insights for infrastructure investments in hydrogen production, storage, transmission, and CO2 capture and storage. The mixed-integer linear programming (MILP) model aims to minimize total system cost with detailed spatiotemporal resolution to meet hydrogen demand in Great Britain. Uncertainty is considered in hydrogen demand, gas, and technology costs, as well as renewables and biomass availability. To address the resulting combinatorial complexity, scenarios are reduced using forward scenario reduction. Optimization results indicate that a combination of autothermal reforming and biomass gasification with carbon capture and storage (CCS) is the most cost-efficient strategy under uncertainty. A what-if analysis explores the impact of water electrolysis penetration on the production mix. The results demonstrate that considering uncertainties provides a risk-averse strategy for decision-making in low-carbon hydrogen pathways.
| Type: | Article |
|---|---|
| Title: | Optimization Approach for Hydrogen Infrastructure Planning Under Uncertainty |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1021/acs.iecr.4c04211 |
| Publisher version: | https://doi.org/10.1021/acs.iecr.4c04211 |
| Language: | English |
| Additional information: | Copyright © 2025 The Authors. Published by American Chemical Society. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Science & Technology, Technology, Engineering, Chemical, Engineering, SUPPLY CHAIN NETWORK, SCENARIO REDUCTION, ENERGY SYSTEM, DESIGN, OPERATION, WIND, FRAMEWORK, STORAGE, HEAT |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10219350 |
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