Virtual 3D City models are increasingly being used for different application areas like urban planning, mobile telecommunication, tourism, disaster management, pedestrian navigation and so on. In recent years most models have been defined purely by their geographical or geometrical aspects, however these models can mostly be used for visualization purposes only. Semantic 3D city models, on the other hand, do not only refer to geometry: all objects included are also described by semantics (e.g. building type, usage, construction date) and topology (e.g. adjacency to other buildings, shared walls), allowing for thematic queries and analysis tasks. With this in mind, the Open Geospatial Consortium (OGC) CityGML standard is designed as an open data model and XML-based format for storage, manipulation, presentation and data exchange of semantic city models at urban and territorial scale. It can further be extended by means of so-called Application Domain Extensions (ADE). This possibility represents a useful characteristic of CityGML: depending on the specific needs, new features or properties can be added. The increasing international acceptance and diffusion of CityGML is proven by the steadily growing number of cities, universities and other research centers, as well as private companies, which are creating and using semantic virtual 3D city models, where CityGML plays more and more an important role as a means to deliver integrated, harmonized and coherent data, which can thus be stored in a centralized, shared database so, that multiple entities of different areas (both public and private) can profit from it. For example, city-wide energy planning requires a precise understanding of the complex system interdependencies at urban level with regards to demand and supply of energy resources, including their spatial distribution. The identification of energetically inefficient buildings therefore plays an important role. Identifying those buildings by modelling their energy performance enables, for example, building professionals to optimize the building design with regard to energy efficiency or at wider scale to define policies at block/district/quartier scale to improve the overall energy demand. Nowadays, a quite large number of specific tools (i.e. software simulation tools) already exist to assess a single building, but their use at urban scale, therefore with multiple buildings and profiting from existing data coming from a semantic 3D city model, is still lacking. Furthermore, the input data, both geometrically and thematically, generally still needs to be prepared manually for each building simulation scenario. The underlying idea of this work is to couple such a simulation tool (namely, Energy Plus) with an already existing CityGML-based 3D city database, in order to exploit the amount of data already available and automatize data ETL (extract transform and load) process, and therefore the whole pipeline enabling the energy simulation of the buildings. The proposed solution includes the conceptual modeling and implementation of an interface able to transfer data bi-directionally between CityGML (and its Energy ADE) and the energy simulation software EnergyPlus. The Energy ADE is being developed by an international consortium of academic and private partners with the goal of extending and enriching CityGML with all those features and attributes that are relevant for energy simulations. EnergyPlus is a whole-building energy simulation program widely used and adopted internationally to model energy and water use in buildings. EnergyPlus can greatly profit from the amount of integrated information that a CityGML/Energy ADE-based model can offer, ranging from geometries to all other relevant energy-related features and attributes. In order to achieve the proposed solution, the following steps are necessary. The CityGML classes will be evaluated and understood, as well as the EnergyPlus Input Data Format. After the evaluation of the existing classes, CityGML classes (and subsequently the Energy ADE as well) need to be mapped into the appropriate EnergyPlus counterpart. In case of missing classes and or missing data, appropriate assumptions need to be made. Afterwards the format of the EnergyPlus simulation results needs to be evaluated, in order to be able to define an interface to translate meaningful results back into CityGML. The last step includes the testing of the bidirectional data interface and the evaluation of the results. Discussed will be under which prerequisites good results can be expected, as well as the pitfalls to be avoided.
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|Publikationsstatus||Veröffentlicht - 2017|
- Nicht definiert