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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2503.05735 |
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| _version_ | 1866912265452650496 |
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| author | Coppitters, Diederik Wiest, Gabriel Göke, Leonard Contino, Francesco Bardow, André Moret, Stefano |
| author_facet | Coppitters, Diederik Wiest, Gabriel Göke, Leonard Contino, Francesco Bardow, André Moret, Stefano |
| contents | Disruptions in energy imports, backlash in social acceptance, and novel technologies failing to develop are unexpected events that are often overlooked in energy planning, despite their ability to jeopardize the energy transition. We propose a method to explore unexpected events and assess their impact on the transition pathway of a large-scale whole-energy system. First, we evaluate unexpected events assuming "perfect foresight", where decision-makers can anticipate such events in advance. This allows us to identify dealbreakers, i.e., conditions that make the transition infeasible. Then, we assess the events under "limited foresight" to evaluate the robustness of early-stage decisions against unforeseen unexpected events and the costs associated with managing them. A case study for Belgium demonstrates that a lack of electrofuel imports in 2050 is the main dealbreaker, while accelerating the deployment of renewables is the most robust policy. Our transferable method can help policymakers identify key dealbreakers and devise robust energy transition policies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_05735 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Identifying Dealbreakers and Robust Policies for the Energy Transition Amid Unexpected Events Coppitters, Diederik Wiest, Gabriel Göke, Leonard Contino, Francesco Bardow, André Moret, Stefano Computers and Society Machine Learning Physics and Society Disruptions in energy imports, backlash in social acceptance, and novel technologies failing to develop are unexpected events that are often overlooked in energy planning, despite their ability to jeopardize the energy transition. We propose a method to explore unexpected events and assess their impact on the transition pathway of a large-scale whole-energy system. First, we evaluate unexpected events assuming "perfect foresight", where decision-makers can anticipate such events in advance. This allows us to identify dealbreakers, i.e., conditions that make the transition infeasible. Then, we assess the events under "limited foresight" to evaluate the robustness of early-stage decisions against unforeseen unexpected events and the costs associated with managing them. A case study for Belgium demonstrates that a lack of electrofuel imports in 2050 is the main dealbreaker, while accelerating the deployment of renewables is the most robust policy. Our transferable method can help policymakers identify key dealbreakers and devise robust energy transition policies. |
| title | Identifying Dealbreakers and Robust Policies for the Energy Transition Amid Unexpected Events |
| topic | Computers and Society Machine Learning Physics and Society |
| url | https://arxiv.org/abs/2503.05735 |