Planning minimum regret $CO_2$ pipeline networks
Stephan Bogs, Ali Abdelshafy, Grit Walther

TL;DR
This paper presents a novel optimization model for planning $CO_2$ pipeline networks that minimizes regret under deep uncertainty, considering upgrade options and applied to Germany's industrial sectors.
Contribution
It introduces a new model that optimizes incremental pipeline development with regret minimization, addressing deep uncertainty and infrastructure upgrade options.
Findings
The model effectively balances infrastructure investment and flexibility.
Application to Germany's industries demonstrates practical utility.
Quantifies trade-offs in pipeline development strategies.
Abstract
The transition to a low-carbon economy necessitates effective carbon capture and storage (CCS) solutions, particularly for hard-to-abate sectors. Herein, pipeline networks are indispensable for cost-efficient transportation over long distances. However, there is deep uncertainty regarding which industrial sectors will participate in such systems. This poses a significant challenge due to substantial investments as well as the lengthy planning and development timelines required for pipeline projects, which are further constrained by limited upgrade options for already built infrastructure. The economies of scale inherent in pipeline construction exacerbate these challenges, leading to potential regret over earlier decisions. While numerous models were developed to optimize the initial layout of pipeline infrastructure based on known demand, a gap exists in addressing the…
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Carbon Dioxide Capture Technologies · Personal Information Management and User Behavior
