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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.03021 |
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| _version_ | 1866916310548480000 |
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| author | Braun, Martin Gruhl, Christian Hans, Christian A. Härtel, Philipp Scholz, Christoph Sick, Bernhard Siefert, Malte Steinke, Florian Stursberg, Olaf Berg, Sebastian Wende-von |
| author_facet | Braun, Martin Gruhl, Christian Hans, Christian A. Härtel, Philipp Scholz, Christoph Sick, Bernhard Siefert, Malte Steinke, Florian Stursberg, Olaf Berg, Sebastian Wende-von |
| contents | Future energy systems are subject to various uncertain influences. As resilient systems they should maintain a constantly high operational performance whatever happens. We explore different levels and time scales of decision making in energy systems, highlighting different uncertainty sources that are relevant in different domains. We discuss how the uncertainties can be represented and how one can react to them. The article closes by summarizing, which uncertainties are already well examined and which ones still need further scientific inquiry to obtain resilient energy systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03021 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems Braun, Martin Gruhl, Christian Hans, Christian A. Härtel, Philipp Scholz, Christoph Sick, Bernhard Siefert, Malte Steinke, Florian Stursberg, Olaf Berg, Sebastian Wende-von Systems and Control Future energy systems are subject to various uncertain influences. As resilient systems they should maintain a constantly high operational performance whatever happens. We explore different levels and time scales of decision making in energy systems, highlighting different uncertainty sources that are relevant in different domains. We discuss how the uncertainties can be represented and how one can react to them. The article closes by summarizing, which uncertainties are already well examined and which ones still need further scientific inquiry to obtain resilient energy systems. |
| title | Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2407.03021 |