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dc.contributor.authorRodríguez Matas, Antonio Franciscoes-ES
dc.contributor.authorLinares Llamas, Pedroes-ES
dc.contributor.authorDomínguez Barbero, Claudiaes-ES
dc.date.accessioned2025-12-17T05:13:55Z
dc.date.available2025-12-17T05:13:55Z
dc.date.issued2026-03-01es_ES
dc.identifier.issn0301-4215es_ES
dc.identifier.urihttps:doi.org10.1016j.enpol.2025.115008es_ES
dc.identifier.urihttp://hdl.handle.net/11531/107775
dc.descriptionArtículos en revistases_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 study aims to develop and demonstrate a structured decision-support framework for designing robust energy policy packages under deep uncertainty. The proposed 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.es-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 study aims to develop and demonstrate a structured decision-support framework for designing robust energy policy packages under deep uncertainty. The proposed 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/octet-streames_ES
dc.language.isoen-GBes_ES
dc.sourceRevista: Energy Policy, Periodo: 1, Volumen: online, Número: , Página inicial: 115008-1, Página final: 115008-14es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleDesigning robust energy policy packages under deep uncertainty: A multi-metric decision support frameworkes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.holderes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.keywordsEnergy policy; Robust decision-making; Policy package design; Deep uncertainty; Decision-support methodses-ES
dc.keywordsEnergy policy; Robust decision-making; Policy package design; Deep uncertainty; Decision-support methodsen-GB


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