Development of a systematic framework for planning carbon capture, utilization and storage (CCUS) systems

Carbon capture, utilization and storage (CCUS) is one of the key emerging strategies to mitigate climate change. It involves capturing of CO2 from industrial sources, and then allocating it to different options for utilization and/or storage. CCUS consists of options for reducing greenhouse gas emis...

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Bibliographic Details
Main Author: Tapia, John Frederick
Format: text
Language:English
Published: Animo Repository 2017
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Online Access:https://animorepository.dlsu.edu.ph/etd_doctoral/496
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Institution: De La Salle University
Language: English
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Summary:Carbon capture, utilization and storage (CCUS) is one of the key emerging strategies to mitigate climate change. It involves capturing of CO2 from industrial sources, and then allocating it to different options for utilization and/or storage. CCUS consists of options for reducing greenhouse gas emissions through storage (CCS) and for securing resources through utilization (CCU) in some cases, storage and utilization can be achieved simultaneously. Economic barriers in CCS deployment can be addressed by additional revenue generated in CCU. Integrating options for utilization and storage requires systematic planning to maximize both economic performance of the system and optimizing CO2 sequestration. To date, quantitative planning frameworks using process systems engineering (PSE) tools have been developed only for CCS, but not for CCUS. This dissertation develops a systematic framework for high-level preliminary planning CCUS systems. Prior to developing a detailed engineering design, this framework involves planning of CO2 allocation, operations scheduling and economic optimization. The framework consists of two mixed integer linear programming (MILP) models for high-level planning. The first MILP model is a discrete-time scheduling model addressing flow rate variations and economic discounting. The second MILP model is a continuous-time scheduling model based on strip packing analogy with better computational performance than the discrete-time approach. These models can be used to develop initial plans for the system. Then, an optimal revamp strategy is developed to adjust the initial plan considering new information introduced in the middle of the planning horizon. Case studies are presented to illustrate this modeling framework. This integrated framework allows the decision maker to gain insights for subsequently developing detailed engineering design of CCUS system. This systematic framework serves as a main tool for decision makers in planning large-scale deployment of CCUS technology.