Multi-objective economic and environmental assessment for the preliminary design of CO2 transport pipelines

被引:13
|
作者
Zanobetti, Francesco [1 ,2 ]
Martynov, Sergey [1 ]
Cozzani, Valerio [2 ]
Mahgerefteh, Haroun [1 ]
机构
[1] UCL, Dept Chem Engn, London WC1E 7JE, England
[2] Univ Bologna, Dept Civil Chem Environm & Mat Engn, LISES Lab Ind Safety & Environm Sustainabil, Via Terracini 28, I-40131 Bologna, Italy
关键词
Carbon capture and storage; CO2 pipelines preliminary design; CO2 pipeline transport; Multi-objective optimisation; Techno-economic assessment; Environmental assessment; CARBON CAPTURE; GHG EMISSIONS; GAS; OPTIMIZATION; TECHNOLOGIES; COST; CCS; INFRASTRUCTURE; BENCHMARKING; ELECTRICITY;
D O I
10.1016/j.jclepro.2023.137330
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A methodology based on the multi-objective optimisation of economic and environmental aspects is presented to support the preliminary design of CO2 transport pipelines employed as part of Carbon Capture and Storage (CCS) systems. Pareto optimal design solutions are determined for a realistic point-to-point CO2 pipeline using Level Diagrams and choosing the Nominal Pipe Size (NPS) as a decision variable. A quantitative procedure entailing the definition of economic and environmental key performance indicators is defined to allow the identification of an optimum pipeline design. The outcome is compared against the minimisation of single-objective indicators based on the CO2 avoided and carbon pricing concepts. The results of a case-study concerning a 70 km long pipeline transporting 10 Mt yr(-1) of supercritical CO2 show that the multi-objective method yields an optimum NPS equal to 30, higher than the NPS 28 deriving from the alternative indexing methods. The proposed mul-ticriteria approach effectively considers case-specific environmental sustainability constraints, which result in determining 46% of the overall performance measure of the identified optimum solution. The results show that conventional single-objective methods underestimate the contribution of environmental factors up to 2.6% of the overall performance index value. A Monte Carlo probabilistic analysis is performed to verify the robustness of the results with respect to the possible uncertainties.
引用
收藏
页数:11
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