Modeling Robust Energy Systems Considering Weather Uncertainty and Nuclear Power Failures: A Case Study in Northern Europe
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866910908927705088 |
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| author | Forghani, Kamran Kan, Xiaoming Reichenberg, Lina Hedenus, Fredrik |
| author_facet | Forghani, Kamran Kan, Xiaoming Reichenberg, Lina Hedenus, Fredrik |
| contents | Capacity expansion models used for policy support have increasingly represented both the variability and uncertainty of weather-dependent generation (wind and solar). However, although also uncertain, as demonstrated by the performance of the French nuclear power fleet in 2022, uncertainty arising from nuclear power outages has been largely neglected in the literature. This paper presents the first capacity expansion model that considers uncertainty in nuclear power availability caused by unplanned outages. We propose a mathematical model that combines a scenario-based stochastic optimization approach (to deal with weather-related uncertainties) with a data-driven adjustable robust optimization approach (to deal with nuclear failure-related uncertainties). The robust model represents the bulky behavior of nuclear power plants, with large (1 GW) units that are either on or off, while at the same time letting the model decide on the optimal amount of nuclear capacity. We tested the model in a case for Northern Europe (seven nodes) with a time resolution of 1250 time steps. Our findings show that nuclear power outages do, in fact, impose a vulnerability on the energy system if not considered in the planning phase. Our proposed model performs well and finds solutions that prevent Loss-of-Load (at a price of robustness of 0.6%), even in more extreme weather conditions. Robust solutions are characterized by a higher capacity of gas plants, but, perhaps surprisingly, nuclear power capacity is barely affected. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08145 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modeling Robust Energy Systems Considering Weather Uncertainty and Nuclear Power Failures: A Case Study in Northern Europe Forghani, Kamran Kan, Xiaoming Reichenberg, Lina Hedenus, Fredrik Optimization and Control Capacity expansion models used for policy support have increasingly represented both the variability and uncertainty of weather-dependent generation (wind and solar). However, although also uncertain, as demonstrated by the performance of the French nuclear power fleet in 2022, uncertainty arising from nuclear power outages has been largely neglected in the literature. This paper presents the first capacity expansion model that considers uncertainty in nuclear power availability caused by unplanned outages. We propose a mathematical model that combines a scenario-based stochastic optimization approach (to deal with weather-related uncertainties) with a data-driven adjustable robust optimization approach (to deal with nuclear failure-related uncertainties). The robust model represents the bulky behavior of nuclear power plants, with large (1 GW) units that are either on or off, while at the same time letting the model decide on the optimal amount of nuclear capacity. We tested the model in a case for Northern Europe (seven nodes) with a time resolution of 1250 time steps. Our findings show that nuclear power outages do, in fact, impose a vulnerability on the energy system if not considered in the planning phase. Our proposed model performs well and finds solutions that prevent Loss-of-Load (at a price of robustness of 0.6%), even in more extreme weather conditions. Robust solutions are characterized by a higher capacity of gas plants, but, perhaps surprisingly, nuclear power capacity is barely affected. |
| title | Modeling Robust Energy Systems Considering Weather Uncertainty and Nuclear Power Failures: A Case Study in Northern Europe |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2504.08145 |