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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2604.19676 |
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- Energy systems optimisation models are a leading tool for informing decisions in the energy transition. However, these models often remain opaque, and results are frequently presented without a clear discussion of their epistemic limitations. We propose Diagnostic Modelling as a framework wherein modellers critically interrogate their models and explore uncertainties to uncover mechanistic explanations that offer policy-relevant insights. Mechanistic explanations provide fundamental understanding that remains valid despite model uncertainty and does not depend on detailed knowledge of a specific model. By adopting a more open and transparent approach to engaging with energy systems models, Diagnostic Modelling encourages the participation of a broader range of decision-makers, thereby building consensus in support of the energy transition.