Perpustakaan Digital ITB

This study aims to evaluate and compare two different approach of pressure drop calculation for CO? transport in pipeline-based CCS systems, the fixed pressure drop method and a realistic segmented pressure drop approach. The study is conducted in the context of Indonesia’s developing CCS infrastructure, focusing on optimizing booster pump requirements and pipeline configuration for power plant emissions. An optimization model using Mixed Integer Linear Programming (MILP) is developed to determine the most efficient source-sink pairings, C CO? flow rates, pipeline diameters, and booster station placement. The MILP modelling is constructed with fixed pressure approach. After initial optimization, post processing using Python Modelling is constructed to re-calculate pressure drop using realistic segmented pressure drop approach, dynamically integrating CO? thermophysical properties via CoolProp Library and applying six friction factor correlations: Colebrook-White, Moody, Zigrang & Sylvester, Chen, Wood, and Blasius. Results show that the fixed pressure drop method significantly overestimates booster pump needs, particularly for small diameter, high flow pipelines. The segmented method offers more conservative yet cost-effective results, typically only one booster per 350+ km route with large diameters. Friction factor choice affect results in the fixed method but has minimal impact under realistic modelling, indicating more stable results. The study highlights the pitfalls of relying solely on static assumptions and underscores the need for thermodynamically informed design. This study contributes new comparative insights between pressure drop methodologies for CCS pipeline systems, offering a replicable model that accounts for dynamic CO? behavior. The findings can guide more cost-effective and technically sound infrastructure development, particularly relevant for emerging economies like Indonesia where CCS investment must be bot scalable and efficient.