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3948. A new modelling framework for offshore energy systems considering decarbonisation and decommissioning options for oil and gas infrastructure: a UK North Sea case study
Invited abstract in session MC-19: Multi-energy systems, stream OR in Energy.
Monday, 12:30-14:00Room: 44 (building: 116)
Authors (first author is the speaker)
| 1. | Anna Peecock
|
| School of Engineering, University of Aberdeen | |
| 2. | Josef Koell
|
| ETH Zurich | |
| 3. | Pietro Bianchi Marzoli
|
| ETH Zurich | |
| 4. | Jiangyi Huang
|
| Chair of Energy Systems Analysis, Department of Mechanical and Process Engineering, ETH Zurich | |
| 5. | Alfonso Martinez-Felipe
|
| Chemical Materials and Processes Group, Just Transition Lab, School of Engineering, University of Aberdeen | |
| 6. | Russell McKenna
|
| Laboratory for Energy Systems Analysis, Paul Scherrer Institute |
Abstract
Exploiting synergies between the offshore wind and oil and gas (O&G) sectors can support decarbonisation goals, whilst exploiting disused hydrocarbon infrastructure for long-term economic value. Incorporating greater sectoral integration and diversity of energy carriers enables energy models to evaluate the impact of different policy levers more realistically. We therefore seek to quantify the economic and environmental benefits achievable by exploiting future synergies between the O&G and offshore wind sectors. This paper analyses scenarios with competing decarbonisation and repurposing alternatives and the resulting impacts on brownfield electrification and offshore hydrogen/ammonia production feasibility, as well as energy demands and emissions in the UK North Sea. Based on a mixed-integer linear programming (MILP) approach, the model determines optimal pathways for each of 242 O&G platforms while minimising total system costs up to 2060. Operational constraints ensure technical viability of proposed technologies and through consideration of multiple energy carriers, a more realistic assessment of energy system integration is undertaken compared to previous studies. Offshore heat and power demands are calculated on a platform-specific level, and wind deployment scenarios are devised using a spatially-constrained bottom-up LCOE model. Future work should focus on integrating this tool within large-scale energy models, to improve the representation of the offshore system.
Keywords
- OR in Energy
- Optimization Modeling
Status: accepted
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