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dc.contributor.authorRosa, Luca dees-ES
dc.contributor.authorMateo Domingo, Carloses-ES
dc.contributor.authorGómez San Román, Tomáses-ES
dc.contributor.authorEl Kontar, Rawades-ES
dc.contributor.authorPolly, Benes-ES
dc.contributor.authorFleming, Katherinees-ES
dc.contributor.authorElgindy, Tarekes-ES
dc.date.accessioned2021-06-07T12:08:35Z
dc.date.available2021-06-07T12:08:35Z
dc.identifier.urihttp://hdl.handle.net/11531/56210
dc.description.abstractes-ES
dc.description.abstractThe increase of greenhouse emissions caused by a rise in global energy consumption is pushing the scientific community to develop tools that address key environmental, techno-economic and social issues. One specific area of focus is to create tools that enable the design of high-performance energy districts, including grid-interactive efficient buildings and electrical distribution infrastructure. This paper outlines the approach of integrating a synthetic distribution network tool (RNM-US) with URBANopt™, a modular and customizable software development kit for thermal and electrical modelling of buildings and energy systems at a district scale. First, we describe the algorithms implemented to integrate RNM-US with URBANopt to automatically generate the distribution network for the district considered. Following, we present a case study for the potential uses of the RNM-US integrations with URBANopt, highlighting the capabilities for economic and technical analysis of the distribution network built in relation to the electricity needs of the modelled buildings.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.titleIntegrated models for electrical distribution network planning and district-scale building energy usees_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.keywordsDistribution Network Planning, Grid-Interactive Efficient Buildings, Smart Districts, URBANopt, RNM-USen-GB


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