Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification
In this paper, we propose a multi-RREH (Remote Renewable Energy Hub) based optimization framework. This framework allows a valorization of CO2 using carbon capture technologies. This valorization is grounded on the idea that CO2 gathered from the atmosphere or post combustion can be combined with hy...
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ftorbi:oai:orbi.ulg.ac.be:2268/309679 2024-04-21T08:03:54+00:00 Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification Dachet, Victor Benzerga, Amina Coppitters, Diederik Contino, Francesco Fonteneau, Raphaël Ernst, Damien 2023 https://orbi.uliege.be/handle/2268/309679 https://orbi.uliege.be/bitstream/2268/309679/1/Dachet2023TowardsCO2Uncertainty.pdf en eng https://orbi.uliege.be/handle/2268/309679 info:hdl:2268/309679 https://orbi.uliege.be/bitstream/2268/309679/1/Dachet2023TowardsCO2Uncertainty.pdf open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess Energy Remote Renewable Energy Hub Optimisation Power-to-X Engineering computing & technology Ingénierie informatique & technologie Energie working paper http://purl.org/coar/resource_type/c_8042 info:eu-repo/semantics/preprint 2023 ftorbi 2024-03-27T14:59:27Z In this paper, we propose a multi-RREH (Remote Renewable Energy Hub) based optimization framework. This framework allows a valorization of CO2 using carbon capture technologies. This valorization is grounded on the idea that CO2 gathered from the atmosphere or post combustion can be combined with hydrogen to produce synthetic methane. The hydrogen is obtained from water electrolysis using renewable energy (RE). Such renewable energy is generated in RREHs, which are locations where RE is cheap and abundant (e.g., solar PV in the Sahara Desert, or wind in Greenland). We instantiate our framework on a case study focusing on Belgium and 2 RREHs, and we conduct a techno-economic analysis under uncertainty. This analysis highlights, among others, the interest in capturing CO2 via Post Combustion Carbon Capture (PCCC) rather than only through Direct Air Capture (DAC) for methane synthesis in RREH. By doing so, a notable reduction of 10% is observed in the total cost of the system under our reference scenario. In addition, we use our framework to derive a carbon price threshold above which carbon capture technologies may start playing a pivotal role in the decarbonation process of our industries. For example, this price threshold may give relevant information for calibrating the EU Emission Trading System so as to trigger the emergence of the multi-RREH. Report Greenland University of Liège: ORBi (Open Repository and Bibliography) |
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Open Polar |
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University of Liège: ORBi (Open Repository and Bibliography) |
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ftorbi |
language |
English |
topic |
Energy Remote Renewable Energy Hub Optimisation Power-to-X Engineering computing & technology Ingénierie informatique & technologie Energie |
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Energy Remote Renewable Energy Hub Optimisation Power-to-X Engineering computing & technology Ingénierie informatique & technologie Energie Dachet, Victor Benzerga, Amina Coppitters, Diederik Contino, Francesco Fonteneau, Raphaël Ernst, Damien Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
topic_facet |
Energy Remote Renewable Energy Hub Optimisation Power-to-X Engineering computing & technology Ingénierie informatique & technologie Energie |
description |
In this paper, we propose a multi-RREH (Remote Renewable Energy Hub) based optimization framework. This framework allows a valorization of CO2 using carbon capture technologies. This valorization is grounded on the idea that CO2 gathered from the atmosphere or post combustion can be combined with hydrogen to produce synthetic methane. The hydrogen is obtained from water electrolysis using renewable energy (RE). Such renewable energy is generated in RREHs, which are locations where RE is cheap and abundant (e.g., solar PV in the Sahara Desert, or wind in Greenland). We instantiate our framework on a case study focusing on Belgium and 2 RREHs, and we conduct a techno-economic analysis under uncertainty. This analysis highlights, among others, the interest in capturing CO2 via Post Combustion Carbon Capture (PCCC) rather than only through Direct Air Capture (DAC) for methane synthesis in RREH. By doing so, a notable reduction of 10% is observed in the total cost of the system under our reference scenario. In addition, we use our framework to derive a carbon price threshold above which carbon capture technologies may start playing a pivotal role in the decarbonation process of our industries. For example, this price threshold may give relevant information for calibrating the EU Emission Trading System so as to trigger the emergence of the multi-RREH. |
format |
Report |
author |
Dachet, Victor Benzerga, Amina Coppitters, Diederik Contino, Francesco Fonteneau, Raphaël Ernst, Damien |
author_facet |
Dachet, Victor Benzerga, Amina Coppitters, Diederik Contino, Francesco Fonteneau, Raphaël Ernst, Damien |
author_sort |
Dachet, Victor |
title |
Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
title_short |
Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
title_full |
Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
title_fullStr |
Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
title_full_unstemmed |
Towards CO2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
title_sort |
towards co2 valorization in a multi remote renewable energy hub framework with uncertainty quantification |
publishDate |
2023 |
url |
https://orbi.uliege.be/handle/2268/309679 https://orbi.uliege.be/bitstream/2268/309679/1/Dachet2023TowardsCO2Uncertainty.pdf |
genre |
Greenland |
genre_facet |
Greenland |
op_relation |
https://orbi.uliege.be/handle/2268/309679 info:hdl:2268/309679 https://orbi.uliege.be/bitstream/2268/309679/1/Dachet2023TowardsCO2Uncertainty.pdf |
op_rights |
open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess |
_version_ |
1796943574686760960 |