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dc.contributor.authorWogrin, Sonjaes-ES
dc.contributor.authorTejada Arango, Diego Alejandroes-ES
dc.contributor.authorGaugl, Robertes-ES
dc.contributor.authorKlatzer, Thomases-ES
dc.contributor.authorBachhiesl, Udoes-ES
dc.date.accessioned2024-02-23T13:40:31Z-
dc.date.available2024-02-23T13:40:31Z-
dc.date.issued2022-07-01es_ES
dc.identifier.issn2352-7110es_ES
dc.identifier.urihttps:doi.org10.1016j.softx.2022.101141es_ES
dc.descriptionArtículos en revistases_ES
dc.description.abstractes-ES
dc.description.abstractThis paper introduces the open-source Low-carbon Expansion Generation Optimization (LEGO) model. It is a multi-purpose tool to carry out numerous techno-economic analyses of the energy sector, ranging from short-term unit commitment to long-term generation and transmission expansion planning. Its highly flexible temporal structure permits both chronological and representative periods. LEGO is composed of thematic blocks that can be combined freely via data options: unit commitment constraints; DC- or AC-OPF formulations; battery degradation; rate of change of frequency inertia constraints; demand-side management; or Power-to-X in the form of the hydrogen sector. This unique feature allows to incorporate highly technical aspects into long-term investment analyses. To our knowledge there is no open-source model that offers this flexibility, which we hereby make freely available to the scientific community.en-GB
dc.format.mimetypeapplication/octet-streames_ES
dc.language.isoen-GBes_ES
dc.sourceRevista: SoftwareX, Periodo: 1, Volumen: online, Número: , Página inicial: 101141-1, Página final: 101141-7es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleLEGO: The open-source Low-carbon Expansion Generation Optimization modeles_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.keywordses-ES
dc.keywordsEnergy system planning software; Open-source; Power system optimization; GitHuben-GB
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