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dc.contributor.authorRodríguez Matas, Antonio Franciscoes-ES
dc.contributor.authorLinares Llamas, Pedroes-ES
dc.contributor.authorDomínguez Barbero, Davides-ES
dc.date.accessioned2025-09-26T16:57:06Z
dc.date.available2025-09-26T16:57:06Z
dc.identifier.urihttp://hdl.handle.net/11531/104964
dc.description.abstractes-ES
dc.description.abstractThe complexity of transitioning to sustainable energy systems requires policy frameworks capable of balancing multiple objectives while addressing deep uncertainty. However, existing approaches often lack systematic methods to identify combinations of policy levers that remain effective across a wide range of uncertain futures. This paper presents a novel decision support framework that guides the selection of robust policy packages based on their performance across multiple objectives under uncertainty. Our method leverages a large ensemble of scenarios and applies scenario discovery techniques to identify influential policy levers. We introduce new indicators to assess the robustness of policies by evaluating their ability to mitigate adverse outcomes across metrics. These indicators support an iterative process to build a robust policy package. Finally, we map the technological and energy pathways associated with the robust policy package by leveraging an energy system optimization model. We illustrate the application of this framework to the Spanish energy system, providing insights into how specific combinations of policy levers shape decarbonization pathways under uncertainty.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.titleNavigating uncertainty in the energy transition: Evaluating policy levers for robust decarbonization strategieses_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES
dc.description.versioninfo:eu-repo/semantics/draftes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsEnergy policy, Robust decision-making, Policy package design, Deep uncertainty, Decision-support method.en-GB


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