Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector

Carbon capture and storage (CCS) is one of the interim technologies to mitigate greenhouse gas emissions from stationary sources such as power plant and large industrial facilities. CCS allows for continued utilization of fossil fuels (e.g. coal, natural gas and oil), which are still relatively inex...

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Main Authors: Tan, Raymond Girard R., Ng, Denny K.S., Foo, Dominic C. Y., Aviso, Kathleen B.
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Published: Animo Repository 2010
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/2475
https://animorepository.dlsu.edu.ph/context/faculty_research/article/3474/type/native/viewcontent
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-34742022-06-22T02:25:46Z Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector Tan, Raymond Girard R. Ng, Denny K.S. Foo, Dominic C. Y. Aviso, Kathleen B. Carbon capture and storage (CCS) is one of the interim technologies to mitigate greenhouse gas emissions from stationary sources such as power plant and large industrial facilities. CCS allows for continued utilization of fossil fuels (e.g. coal, natural gas and oil), which are still relatively inexpensive and reliable in comparison to inherently low-carbon renewable resources (e.g. wind, solar etc.). On the other hand, retrofitting power plants for carbon capture (CC) entails major capital costs as well as reduction of thermal efficiency and power output. This paper presents integer programming optimization models for planning the retrofit of power plants at the regional, sectoral or national level. In addition to the base case (i.e., non-fuzzy or crisp) formulation, two fuzzy extensions are given to account for the inherent conflict between environmental and economic goals, as well as parametric uncertainties pertaining to the emerging CC technologies. Case studies are shown to illustrate the modeling approach. © 2010 The Institution of Chemical Engineers. 2010-12-01T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/2475 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3474/type/native/viewcontent Faculty Research Work Animo Repository Carbon sequestration Greenhouse gas mitigation Chemical Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Carbon sequestration
Greenhouse gas mitigation
Chemical Engineering
spellingShingle Carbon sequestration
Greenhouse gas mitigation
Chemical Engineering
Tan, Raymond Girard R.
Ng, Denny K.S.
Foo, Dominic C. Y.
Aviso, Kathleen B.
Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
description Carbon capture and storage (CCS) is one of the interim technologies to mitigate greenhouse gas emissions from stationary sources such as power plant and large industrial facilities. CCS allows for continued utilization of fossil fuels (e.g. coal, natural gas and oil), which are still relatively inexpensive and reliable in comparison to inherently low-carbon renewable resources (e.g. wind, solar etc.). On the other hand, retrofitting power plants for carbon capture (CC) entails major capital costs as well as reduction of thermal efficiency and power output. This paper presents integer programming optimization models for planning the retrofit of power plants at the regional, sectoral or national level. In addition to the base case (i.e., non-fuzzy or crisp) formulation, two fuzzy extensions are given to account for the inherent conflict between environmental and economic goals, as well as parametric uncertainties pertaining to the emerging CC technologies. Case studies are shown to illustrate the modeling approach. © 2010 The Institution of Chemical Engineers.
format text
author Tan, Raymond Girard R.
Ng, Denny K.S.
Foo, Dominic C. Y.
Aviso, Kathleen B.
author_facet Tan, Raymond Girard R.
Ng, Denny K.S.
Foo, Dominic C. Y.
Aviso, Kathleen B.
author_sort Tan, Raymond Girard R.
title Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
title_short Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
title_full Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
title_fullStr Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
title_full_unstemmed Crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
title_sort crisp and fuzzy integer programming models for optimal carbon sequestration retrofit in the power sector
publisher Animo Repository
publishDate 2010
url https://animorepository.dlsu.edu.ph/faculty_research/2475
https://animorepository.dlsu.edu.ph/context/faculty_research/article/3474/type/native/viewcontent
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