dc.contributor.author | Forouli, Aikaterini | |
dc.contributor.author | Doukas, H. | |
dc.contributor.author | Nikas, A. | |
dc.contributor.author | Sampedro, J. | |
dc.contributor.author | Van de Ven, Dirk-Jan Petrus Adrianus | |
dc.date.accessioned | 2020-10-29T11:36:28Z | |
dc.date.available | 2020-10-29T11:36:28Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Utilities Policy 57: 33-42 (2019) | es_ES |
dc.identifier.issn | 0957-1787 | |
dc.identifier.uri | http://hdl.handle.net/10810/47406 | |
dc.description.abstract | Here, 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 Ltd | es_ES |
dc.description.sponsorship | The 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.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/642260 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/es/ | * |
dc.subject | Decision support; | es_ES |
dc.subject | Portfolio analysis | es_ES |
dc.subject | Power generation | es_ES |
dc.subject | Robustness | es_ES |
dc.subject | Technology R&D | es_ES |
dc.subject | Uncertainty | es_ES |
dc.title | Identifying optimal technological portfolios for European power generation towards climate change mitigation: A robust portfolio analysis approach | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2019 Elsevier Ltd. All rights reserved. | es_ES |
dc.rights.holder | Atribución-NoComercial-CompartirIgual 3.0 España | * |
dc.relation.publisherversion | https://dx.doi.org/10.1016/j.jup.2019.01.006 | es_ES |
dc.contributor.funder | European Commission | |