Development and application of a multi-stage CCUS source–sink matching model
Liang Sun and
Wenying Chen
Applied Energy, 2017, vol. 185, issue P2, 1424-1432
Abstract:
To achieve the targets in the Paris Climate Change Agreement, carbon capture, utilization and storage (CCUS) will be one of the critical carbon mitigation technologies. For China, the biggest carbon emitter with coal-dominated energy structure, CCUS is expected to play more and more important roles for carbon emissions reduction. This paper looks at a method for designing a pipeline network system for large-scale CO2 capture, utilization, and storage (CCUS) in China. On the basis of performing a moderately significant literature review of past papers and models dating back to the early 2000’s, a updated multi-stage mixed integer programming (MIP) model for carbon source and sink matching (SSM) in ChinaCCUS DSS (Decision Support System) is developed. The Jing-Jin-Ji (Beijing–Tianjin–Hebei) region suffering from increasingly serious air pollution is chose as a case study to address the SSM issue with application of the updated model. The modeling results show that around 2200km pipeline with investment of around $1.6billion needed to be built to transport the cumulative sequestrated emissions of 1620Mt CO2 in the planning period of 2020–2050. Compared to the single-stage programming, the multi-stage programming could result to better pipeline connectivity.
Keywords: Carbon capture; Utilization and storage; Source–sink matching; Pipeline network; Decision support system; Multi-stage programming (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261916000209
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:185:y:2017:i:p2:p:1424-1432
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2016.01.009
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().