Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit
This paper analyzes the viability of an offshore energy hub consisting of wind turbines, batteries, fuel cells and electrolyzers connected to, and powering, an oil producing floating production storage and offloading unit. We assess these components considering an oil production setup that strives f...
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The American Society of Mechanical Engineers
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Online Access: | https://hdl.handle.net/11250/3092979 https://doi.org/10.1115/OMAE2023-105003 |
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ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/3092979 2023-10-29T02:32:46+01:00 Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit Abritta Aguiar Santos, Ramon Pavlov, Alexey Varagnolo, Damiano Tore Børresen, Børre 2023 application/octet-stream https://hdl.handle.net/11250/3092979 https://doi.org/10.1115/OMAE2023-105003 eng eng The American Society of Mechanical Engineers https://hdl.handle.net/11250/3092979 https://doi.org/10.1115/OMAE2023-105003 cristin:2179057 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no Proceedings of the ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. Volume 8: Ocean Renewable Energy Journal article 2023 ftntnutrondheimi https://doi.org/10.1115/OMAE2023-105003 2023-10-04T22:46:24Z This paper analyzes the viability of an offshore energy hub consisting of wind turbines, batteries, fuel cells and electrolyzers connected to, and powering, an oil producing floating production storage and offloading unit. We assess these components considering an oil production setup that strives for reduced CO2 emissions. The problem is addressed from a probabilistic perspective. First, we utilize a quasirandom Monte Carlo approach to generate multiple scenarios regarding the uncertainties of the problem. Then, we evaluate the estimated net present value and total CO2 emissions of the system. As a highlight, our method is capable of exploiting a larger variety of data and capturing more sources of uncertainties compared to the literature. Open-source wind data is used to simulate wind power generation. Wind speed is modeled via a kernel density estimator to benefit the most from the data. The obtained results indicate that the renewable energy technologies enable outcomes with significant reduction to CO2 emissions. However, at the current prices of these technologies, operating a low emitting field links to the loss of a significant share of the expected profits. publishedVersion Copyright © 2023 by ASME Article in Journal/Newspaper Arctic NTNU Open Archive (Norwegian University of Science and Technology) Volume 8: Ocean Renewable Energy |
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Open Polar |
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NTNU Open Archive (Norwegian University of Science and Technology) |
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ftntnutrondheimi |
language |
English |
description |
This paper analyzes the viability of an offshore energy hub consisting of wind turbines, batteries, fuel cells and electrolyzers connected to, and powering, an oil producing floating production storage and offloading unit. We assess these components considering an oil production setup that strives for reduced CO2 emissions. The problem is addressed from a probabilistic perspective. First, we utilize a quasirandom Monte Carlo approach to generate multiple scenarios regarding the uncertainties of the problem. Then, we evaluate the estimated net present value and total CO2 emissions of the system. As a highlight, our method is capable of exploiting a larger variety of data and capturing more sources of uncertainties compared to the literature. Open-source wind data is used to simulate wind power generation. Wind speed is modeled via a kernel density estimator to benefit the most from the data. The obtained results indicate that the renewable energy technologies enable outcomes with significant reduction to CO2 emissions. However, at the current prices of these technologies, operating a low emitting field links to the loss of a significant share of the expected profits. publishedVersion Copyright © 2023 by ASME |
format |
Article in Journal/Newspaper |
author |
Abritta Aguiar Santos, Ramon Pavlov, Alexey Varagnolo, Damiano Tore Børresen, Børre |
spellingShingle |
Abritta Aguiar Santos, Ramon Pavlov, Alexey Varagnolo, Damiano Tore Børresen, Børre Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit |
author_facet |
Abritta Aguiar Santos, Ramon Pavlov, Alexey Varagnolo, Damiano Tore Børresen, Børre |
author_sort |
Abritta Aguiar Santos, Ramon |
title |
Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit |
title_short |
Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit |
title_full |
Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit |
title_fullStr |
Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit |
title_full_unstemmed |
Probabilistic Economic Assessment of an Offshore Energy Hub Supplying Electrical Power to a Floating Production Storage and Offloading Unit |
title_sort |
probabilistic economic assessment of an offshore energy hub supplying electrical power to a floating production storage and offloading unit |
publisher |
The American Society of Mechanical Engineers |
publishDate |
2023 |
url |
https://hdl.handle.net/11250/3092979 https://doi.org/10.1115/OMAE2023-105003 |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Proceedings of the ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. Volume 8: Ocean Renewable Energy |
op_relation |
https://hdl.handle.net/11250/3092979 https://doi.org/10.1115/OMAE2023-105003 cristin:2179057 |
op_rights |
Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no |
op_doi |
https://doi.org/10.1115/OMAE2023-105003 |
container_title |
Volume 8: Ocean Renewable Energy |
_version_ |
1781054713619283968 |