An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets
Carbon capture and storage (CCS) is an important technology that can contribute to the reduction of greenhouse gas emissions. It involves the capture of CO2 from point sources such as power plants and subsequent storage in secure geological reservoirs. However, capture incurs parasitic power loss; t...
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Format: | Article |
Language: | English |
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AIDIC Servizi S.r.l.
2021-11-01
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Series: | Chemical Engineering Transactions |
Online Access: | https://www.cetjournal.it/index.php/cet/article/view/11883 |
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author | John Frederick D. Tapia Lea Myka Española Lhyra Zophiya Fernandez Grace Emmanuelle Lontok Leslie Genevieve Ong Raymond R. Tan |
author_facet | John Frederick D. Tapia Lea Myka Española Lhyra Zophiya Fernandez Grace Emmanuelle Lontok Leslie Genevieve Ong Raymond R. Tan |
author_sort | John Frederick D. Tapia |
collection | DOAJ |
description | Carbon capture and storage (CCS) is an important technology that can contribute to the reduction of greenhouse gas emissions. It involves the capture of CO2 from point sources such as power plants and subsequent storage in secure geological reservoirs. However, capture incurs parasitic power loss; thus, compensatory power from clean sources such as renewables will be needed to make up for the power losses. The conventional capture process is designed for steady-state operation, but flexible capture is possible to offset the intermittency of renewable energy. Systematic planning for robust CCS systems is needed to incorporate flexible mechanisms in CO2 capture. In this study, a mixed integer linear program (MILP) is developed to robust CCS retrofit subject to operational adjustments for multiple periods or scenarios. Retrofit decisions include options for flexible and non-flexible capture, accounting for trade-offs between the two options. Operational adjustments pertain to decisions to switch off the flexible capture plants to compensate for depressed renewable energy supply. A case study is presented to demonstrate the optimization model. From the case study, flexible mechanism can provide a more robust planning, where low availabilities of renewable energy can contribute up to 18% of the power demand. |
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id | doaj.art-c08a3ffce4d642729d29f295cf1eb9ee |
institution | Directory Open Access Journal |
issn | 2283-9216 |
language | English |
last_indexed | 2024-12-14T09:24:33Z |
publishDate | 2021-11-01 |
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spelling | doaj.art-c08a3ffce4d642729d29f295cf1eb9ee2022-12-21T23:08:14ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162021-11-018810.3303/CET2188090An Extended MILP Model for Planning CCS Retrofit in Power Plant FleetsJohn Frederick D. TapiaLea Myka EspañolaLhyra Zophiya FernandezGrace Emmanuelle LontokLeslie Genevieve OngRaymond R. TanCarbon capture and storage (CCS) is an important technology that can contribute to the reduction of greenhouse gas emissions. It involves the capture of CO2 from point sources such as power plants and subsequent storage in secure geological reservoirs. However, capture incurs parasitic power loss; thus, compensatory power from clean sources such as renewables will be needed to make up for the power losses. The conventional capture process is designed for steady-state operation, but flexible capture is possible to offset the intermittency of renewable energy. Systematic planning for robust CCS systems is needed to incorporate flexible mechanisms in CO2 capture. In this study, a mixed integer linear program (MILP) is developed to robust CCS retrofit subject to operational adjustments for multiple periods or scenarios. Retrofit decisions include options for flexible and non-flexible capture, accounting for trade-offs between the two options. Operational adjustments pertain to decisions to switch off the flexible capture plants to compensate for depressed renewable energy supply. A case study is presented to demonstrate the optimization model. From the case study, flexible mechanism can provide a more robust planning, where low availabilities of renewable energy can contribute up to 18% of the power demand.https://www.cetjournal.it/index.php/cet/article/view/11883 |
spellingShingle | John Frederick D. Tapia Lea Myka Española Lhyra Zophiya Fernandez Grace Emmanuelle Lontok Leslie Genevieve Ong Raymond R. Tan An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets Chemical Engineering Transactions |
title | An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets |
title_full | An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets |
title_fullStr | An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets |
title_full_unstemmed | An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets |
title_short | An Extended MILP Model for Planning CCS Retrofit in Power Plant Fleets |
title_sort | extended milp model for planning ccs retrofit in power plant fleets |
url | https://www.cetjournal.it/index.php/cet/article/view/11883 |
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