<div class="csl-bib-body">
<div class="csl-entry">Bindreiter, S., Sisman, Y., & Forster, J. (2024). Visualise Energy Saving Potentials in Settlement Development: By linking transport and energy simulation models for municipal planning. In O. Kontovourkis, M. C. Phocas, & G. Wurzer (Eds.), <i>eCAADe 2024. Data-Driven Intelligence. Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe, Volume 2</i> (pp. 79–88). eCAADe (Education and research in Computer Aided Architectural Design in Europe). http://hdl.handle.net/20.500.12708/201330</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/201330
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dc.description.abstract
To achieve Sustainable Development Goals, in addition to the switch to sustainable energy sources and energy-efficient buildings, transport offers a major lever for reducing energy consumption and greenhouse gases. The increasing demand for emission-free mobility (e.g. through electromobility) but also heat pumps has a direct impact on the electricity consumption of buildings and settlements. It is still difficult to simulate the effects and interactions of different measures as sector coupling concepts require comprehensible tools for ex ante evaluation of planning measures at the community level and the linking of domain-specific models (energy, transport). Using the municipality of Bruck an der Leitha (Austria) as an example, a digital twin based on an open data model (Bednar et al., 2020) is created for the development of methods, which can be used to simulate measures to improve the settlement structure within the municipality. Forecast models for mobility (Schmaus, 2019; Ritz, 2019) and the building stock are developed or applied and linked via the open data model to be able to run through development scenarios and variants. The forecasting and visualisation options created in the project form the basis for the ex-ante evaluation of measures and policies on the way to a Positive-Energy-District. By identifying and collecting missing data, data gaps are filled for the simulation of precise models in the specific study area.
A digital, interactive 3D model is created to examine the forecast results and the different scenarios.
en
dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.subject
visualisation
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dc.subject
decision support
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dc.subject
sector coupling
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dc.subject
holistic spatial energy models for municipal planning
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dc.subject
(energy) saving potentials in settlement development
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dc.title
Visualise Energy Saving Potentials in Settlement Development: By linking transport and energy simulation models for municipal planning
en
dc.type
Book Contribution
en
dc.type
Buchbeitrag
de
dc.contributor.affiliation
TU Wien, Austria
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dc.relation.isbn
9789491207389
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dc.description.startpage
79
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dc.description.endpage
88
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dc.relation.grantno
FO999893499_27052022_130430934
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dc.type.category
Edited Volume Contribution
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dc.relation.eissn
2684-1843
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tuw.booktitle
eCAADe 2024. Data-Driven Intelligence. Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe, Volume 2
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tuw.book.ispartofseries
eCAADe proceedings
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tuw.relation.publisher
eCAADe (Education and research in Computer Aided Architectural Design in Europe)
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tuw.project.title
Potentiale der Quartiersentwicklungsplanung auf dem Weg zum Plus-Energie-Quartier
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tuw.researchTopic.id
A2
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tuw.researchTopic.id
E1
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tuw.researchTopic.id
C6
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tuw.researchTopic.name
Urban and Regional Transformation
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tuw.researchTopic.name
Energy Active Buildings, Settlements and Spatial Infrastructures