Project work Yannik Hall (Civil Engineering)
Development of a GIS-based workflow for the automated preparation of building data for energy-related neighborhood analysis
Development of a GIS-based workflow for the automated preparation of building data for energy-related neighborhood analysis
With the entry into force of the Heat Planning Act (WPG) in January 2024, municipal heat planning has become a mandatory task for local authorities. The legally required inventory analysis in accordance with Section 15 WPG and the planning steps based on this require a spatially resolved, simulation-capable building model. The public administrative and geodata available for this purpose - the real estate cadastre (ALKIS), 3D city models (LOD2) and census raster data - are primarily designed for documentary purposes and do not directly meet the requirements of physical simulation environments.
Process diagram workflow
The paper describes how an automated workflow can be designed and implemented to gradually convert these heterogeneous data sources into a consistent, closed 3D building model. To this end, the geometric characteristics of multi-part LOD2 objects and inner courtyards are first discussed and a scoring system for linking 2D cadastre and 3D geometry is described. It is then explained how the resulting building models are enriched with attributes from census grid data (building age classes) and ALKIS (types of use). For further energy parameterization, it is shown how the IWU building typology (construction structures, refurbishment scenarios), the BDEW standard load profiles (internal loads, time curves), DIN V 18599, Destatis occupancy statistics and meteorological test reference years can be structurally integrated. The results are validated visually in the VICUS target system using layering and color coding of the data origin.
Electricity Schedule H0
The described workflow forms the pre-processing for a subsequent cluster simulation in the CityData platform, in which representative buildings are dynamically simulated with NANDRAD and the results are scaled up to the entire neighborhood using metamodels.
Supervision
The work was supervised by Dipl.-Ing. Dirk Weiß.
© Dirk Weiß
Research assistant
NameDipl.-Ing. Dirk Weiss
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