Monte Carlo Sensitivity Analysis for a Carbon Capture, Utilization, and Storage Whole-Process System

被引:0
作者
Han, Zhuo [1 ,2 ]
Liu, Hang [1 ]
Zhao, Dongya [1 ]
Chen, Yurong [1 ]
Xing, Yupeng [1 ]
Zhang, Zixuan [1 ]
机构
[1] China Univ Petr East China, Coll New Energy, Qingdao 266580, Peoples R China
[2] Sinopec Shengli Offshore Petr Engn Inspect Co Ltd, Dongying 257000, Peoples R China
关键词
carbon capture; utilization; and storage (CCUS); enhanced oil recovery (EOR); whole process; economic system; cost model; sensitivity analysis; Sobol' method; Monte Carlo estimation; engineering optimization; ECONOMIC-EVALUATION; CO2; CAPTURE; UNCERTAINTY; MODEL; COST; OPTIMIZATION; TRANSPORTATION; TECHNOLOGY; DESIGN;
D O I
10.3390/pr13051356
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Carbon capture, utilization, and storage (CCUS) is an emerging technology with significant potential for large-scale emissions reduction. To reduce the overall system costs of CCUS, this study first establishes a comprehensive economic cost model for the entire CCUS process. Subsequently, a Monte Carlo-based Sobol' global sensitivity analysis method is proposed to calculate both first-order and total-order sensitivity indices, followed by qualitative and quantitative analyses of parameter sensitivity. Additionally, convergence analyses of the results and their engineering applicability are examined. The findings reveal that the total-order sensitivity indices for electricity price, flue gas inlet flow rate, pipeline diameter, pipeline material price, pipeline inlet pressure, and injection pressure are 0.6578, 0.3857, 0.5585, 0.3823, 0.2205, and 0.1949, respectively, which are significantly higher than those of the other parameters. This indicates that these parameters have a dominant impact on energy consumption costs through the processes of capture and compression, pipeline transportation, and storage injection. These results provide a basis for selecting decision variables when optimizing the entire CCUS process.
引用
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页数:24
相关论文
共 62 条
[1]   The Impact of Carbon Capture Storage and Utilization on Energy Efficiency, Sustainability, and Production of an Offshore Platform: Thermodynamic and Sensitivity Analyses [J].
Allahyarzadeh Bidgoli, Ali ;
Hamidishad, Nayereh ;
Yanagihara, Jurandir Itizo .
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME, 2022, 144 (11)
[2]  
[Anonymous], 2021, Net Zero by 2050-A Roadmap for the Global Energy Sector
[3]   Random forests for global sensitivity analysis: A selective review [J].
Antoniadis, Anestis ;
Lambert-Lacroix, Sophie ;
Poggi, Jean-Michel .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 206
[4]  
Arachchige U.S.P., 2019, Environ. Sci. Chem. Eng
[5]   Comparison of two sets of Monte Carlo estimators of Sobol' indices [J].
Azzini, Ivano ;
Mara, Thierry A. ;
Rosati, Rossana .
ENVIRONMENTAL MODELLING & SOFTWARE, 2021, 144
[6]  
Bagheri M., 2020, APPEA J, V60, P1, DOI [10.1071/AJ19137, DOI 10.1071/AJ19137]
[7]   Carbon dioxide pipeline route optimization for carbon capture, utilization, and storage: A case study for North-Central USA [J].
Balaji, Karthik ;
Rabiei, Minou .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 51
[8]   Post-combustion carbon dioxide capture using membrane processes: A sensitivity analysis [J].
Belaissaoui, B. ;
Willson, D. ;
Favre, E. .
EUROMEMBRANE CONFERENCE 2012, 2012, 44 :1191-1195
[9]   MONTE-CARLO SENSITIVITY ANALYSIS OF INPUT-OUTPUT MODELS [J].
BULLARD, CW ;
SEBALD, AV .
REVIEW OF ECONOMICS AND STATISTICS, 1988, 70 (04) :708-712
[10]   Adaptive use of replicated Latin Hypercube Designs for computing Sobol' sensitivity indices [J].
Damblin, Guillaume ;
Ghione, Alberto .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 212