Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty
In this paper, we study how uncertainties weighing on the climate system impact the optimal technological pathways the world energy system should take to comply with stringent mitigation objectives. We use the TIAM-World model that relies on the TIMES modelling approach. Its climate module is inspir...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/24/8595 |
| _version_ | 1797504958676860928 |
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| author | Claire Nicolas Stéphane Tchung-Ming Olivier Bahn Erick Delage |
| author_facet | Claire Nicolas Stéphane Tchung-Ming Olivier Bahn Erick Delage |
| author_sort | Claire Nicolas |
| collection | DOAJ |
| description | In this paper, we study how uncertainties weighing on the climate system impact the optimal technological pathways the world energy system should take to comply with stringent mitigation objectives. We use the TIAM-World model that relies on the TIMES modelling approach. Its climate module is inspired by the DICE model. Using robust optimization techniques, we assess the impact of the climate system parameter uncertainty on energy transition pathways under various climate constraints. Unlike other studies we consider all the climate system parameters which is of primary importance since: (i) parameters and outcomes of climate models are all inherently uncertain (parametric uncertainty); and (ii) the simplified models at stake summarize phenomena that are by nature complex and non-linear in a few, sometimes linear, equations so that structural uncertainty is also a major issue. The use of robust optimization allows us to identify economic energy transition pathways under climate constraints for which the outcome scenarios remain relevant for any realization of the climate parameters. In this sense, transition pathways are made robust. We find that the abatement strategies are quite different between the two temperature targets. The most stringent one is reached by investing massively in carbon removal technologies such as bioenergy with carbon capture and storage (BECCS) which have yields much lower than traditional fossil fuelled technologies. |
| first_indexed | 2024-03-10T04:11:49Z |
| format | Article |
| id | doaj.art-2074701b8c994e7faf4f4591ecd7cc11 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T04:11:49Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2074701b8c994e7faf4f4591ecd7cc112023-11-23T08:09:27ZengMDPI AGEnergies1996-10732021-12-011424859510.3390/en14248595Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate UncertaintyClaire Nicolas0Stéphane Tchung-Ming1Olivier Bahn2Erick Delage3IFP Energies Nouvelles, 1–4 Avenue de Bois-Préau, 92852 Rueil-Malmaison, FranceIFP Energies Nouvelles, 1–4 Avenue de Bois-Préau, 92852 Rueil-Malmaison, FranceGERAD and Department of Decision Sciences, HEC Montréal, Montreal, QC H3T 2A7, CanadaGERAD and Department of Decision Sciences, HEC Montréal, Montreal, QC H3T 2A7, CanadaIn this paper, we study how uncertainties weighing on the climate system impact the optimal technological pathways the world energy system should take to comply with stringent mitigation objectives. We use the TIAM-World model that relies on the TIMES modelling approach. Its climate module is inspired by the DICE model. Using robust optimization techniques, we assess the impact of the climate system parameter uncertainty on energy transition pathways under various climate constraints. Unlike other studies we consider all the climate system parameters which is of primary importance since: (i) parameters and outcomes of climate models are all inherently uncertain (parametric uncertainty); and (ii) the simplified models at stake summarize phenomena that are by nature complex and non-linear in a few, sometimes linear, equations so that structural uncertainty is also a major issue. The use of robust optimization allows us to identify economic energy transition pathways under climate constraints for which the outcome scenarios remain relevant for any realization of the climate parameters. In this sense, transition pathways are made robust. We find that the abatement strategies are quite different between the two temperature targets. The most stringent one is reached by investing massively in carbon removal technologies such as bioenergy with carbon capture and storage (BECCS) which have yields much lower than traditional fossil fuelled technologies.https://www.mdpi.com/1996-1073/14/24/8595robust optimizationclimate changeclimate modellinguncertaintydecision-making under uncertainty |
| spellingShingle | Claire Nicolas Stéphane Tchung-Ming Olivier Bahn Erick Delage Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty Energies robust optimization climate change climate modelling uncertainty decision-making under uncertainty |
| title | Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty |
| title_full | Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty |
| title_fullStr | Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty |
| title_full_unstemmed | Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty |
| title_short | Robust Enough? Exploring Temperature-Constrained Energy Transition Pathways under Climate Uncertainty |
| title_sort | robust enough exploring temperature constrained energy transition pathways under climate uncertainty |
| topic | robust optimization climate change climate modelling uncertainty decision-making under uncertainty |
| url | https://www.mdpi.com/1996-1073/14/24/8595 |
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