Development and Testing of the CityJSON Energy Extension for Space Heating Demand Calculation

Development and Testing of the CityJSON Energy Extension for Space Heating Demand Calculation

TUFAN, ÖZGE (TU Delft Architecture and the Built Environment)

León Sánchez, C.A. (mentor)
Arroyo Ohori, G.A.K. (graduation committee)
Ledoux, H. (graduation committee)

Delft University of Technology

Geomatics

2022-06-29

3D city models are frequently used to acquire and store energy-related information of buildings to be used in energy applications, such as solar potential analyses and energy demand calculations. In this context, the most common data model is CityGML, which provides an application domain extension called the Energy ADE to store energy-related data in a systematic manner in XML format. On the other hand, CityJSON has been developed as a JSON-based encoding to exchange 3D city models, with the aim of eliminating the hierarchical structure and shortcomings of the XML-based CityGML. However, even though an extension mechanism exists in CityJSON, an energy-related CityJSON extension is not present in the current literature. Therefore, the aim of this thesis is to develop and test a CityJSON Energy Extension. To achieve this, the space heating demand calculation of buildings is chosen as the use case to validate and test the Extension.
In this thesis, a simplified version of the Energy ADE, called the Energy ADE KIT profile, is used as the first step to create a semi-direct translation to a CityJSON Energy Extension. After validating the Extension with the official validator of CityJSON, the space heating demand is calculated for a subset of the Rijssen-Holten in the Netherlands according to the Dutch standard NTA 8800. Required input data is collected from various data sources and stored in the CityJSON Energy Extension to test its usability for the use case. The Extension is then improved depending on the results of the tests based on the use case. The results show that the semi-direct translation lacked numerous objects and attributes to store certain input data, while the final version of the Extension fully supports the use case. Furthermore, while the semi-direct translation contained deep hierarchical structures, these were eliminated in the final Extension to comply with the design decisions behind CityJSON. The main differences between the Energy ADE and the CityJSON Energy Extension reflected this philosophy as well, where the former was built with a deep hierarchical structure, while the latter flattens this hierarchy by using the characteristics of JSON. In addition, a comparison in file sizes showed that the input 3D city model of the study area in CityJSON format had a file size of 40.6 MB, whereas the output CityJSON + Energy Extension file with all input and output data was 65.8 MB. It was discussed that this increase of 25.2 MB in file size is not significant, considering the high increase in the number of objects stored in the file. On the other hand, space heating demand calculation resulted in negative values for 32 buildings in the study area, which was not expected. While the possible reasons were detected, a solution could not be developed in the given time frame of the thesis. Overall, this thesis showed that the CityJSON Energy Extension can provide an easy-to-use alternative to CityGML Energy ADE, where the Extension files can be simply parsed by software and easily understood by the user without reaching large file sizes.

3D city modelling
CityGML
CityJSON
Energy ADE
Urban Energy Modelling
Space heating demand

http://resolver.tudelft.nl/uuid:0061d94c-46b6-4910-bb73-b6cdc9b85f84

Student theses

master thesis

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