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dc.contributor.authorForouli, Aikaterini
dc.contributor.authorDoukas, H.
dc.contributor.authorNikas, A.
dc.contributor.authorSampedro, J.
dc.contributor.authorVan de Ven, Dirk-Jan Petrus Adrianus
dc.date.accessioned2020-10-29T11:36:28Z
dc.date.available2020-10-29T11:36:28Z
dc.date.issued2019
dc.identifier.citationUtilities Policy 57: 33-42 (2019)es_ES
dc.identifier.issn9571787
dc.identifier.urihttp://hdl.handle.net/10810/47406
dc.description.abstractHere, an integrative approach is proposed to link integrated assessment modelling results from the GCAM model with a novel portfolio analysis framework. This framework comprises a bi-objective optimisation model, Monte Carlo analysis and the Iterative Trichotomic Approach, aimed at carrying out stochastic uncertainty assessment and enhancing robustness. The approach is applied for identifying optimal technological portfolios for power generation in the EU towards climate change mitigation until 2050. The considered technologies include photovoltaics, concentrated solar power, wind, nuclear, biomass and carbon capture and storage, for which different subsidy curves for emissions reduction and energy security are considered. © 2019 Elsevier Ltdes_ES
dc.description.sponsorshipThe most important part of this research is based on the H2020 European Commission Project “Transitions pathways and risk analysis for climate change mitigation and adaptation strategies—TRANSrisk” under grant agreement No. 642260 .es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/642260es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.subjectDecision support;es_ES
dc.subjectPortfolio analysises_ES
dc.subjectPower generationes_ES
dc.subjectRobustnesses_ES
dc.subjectTechnology R&Des_ES
dc.subjectUncertaintyes_ES
dc.titleIdentifying optimal technological portfolios for European power generation towards climate change mitigation: A robust portfolio analysis approaches_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2019 Elsevier Ltd. All rights reserved.es_ES
dc.rights.holderAtribución-NoComercial-CompartirIgual 3.0 España*
dc.relation.publisherversionhttps://dx.doi.org/10.1016/j.jup.2019.01.006es_ES
dc.contributor.funderEuropean Commission


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© 2019 Elsevier Ltd. All rights reserved.
Except where otherwise noted, this item's license is described as © 2019 Elsevier Ltd. All rights reserved.