Abstract
With the increased emphasis on decarbonization in recent years, there is a growing interest in the development of sustainable industrial supply chains. With its widespread applications, clean hydrogen holds immense potential to push forward the goal of a net-zero economy. For this reason, we develop mathematical models to optimize the design and planning of low-carbon hydrogen supply chains, specifically when the potential markets are willing to pay certain premiums for hydrogen of different levels of carbon intensity. We introduce the concept of a hydrogen supply chain with virtual distribution of carbon intensities, which allows more cost-effective supply chain operations compared with the conventional model in which different carbon intensities associated with a product can only be achieved through physical blending. Additionally, owing to the difficulty in predicting future hydrogen prices, we propose a multistage stochastic programming framework to account for uncertainty in market prices. The proposed model is applied to a network of hydrogen production plants and potential markets, highlighting differences in decisions across different scenarios.
| Original language | English (US) |
|---|---|
| Title of host publication | Computer Aided Chemical Engineering |
| Publisher | Elsevier B.V. |
| Pages | 3357-3362 |
| Number of pages | 6 |
| DOIs | |
| State | Published - Jan 2023 |
Publication series
| Name | Computer Aided Chemical Engineering |
|---|---|
| Volume | 52 |
| ISSN (Print) | 1570-7946 |
Bibliographical note
Publisher Copyright:© 2023 Elsevier B.V.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 12 Responsible Consumption and Production
Keywords
- hydrogen-based economy
- mixed-integer nonlinear programming
- multistage stochastic programming
- nonconvex optimization
- virtual supply chain
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