SHP2SIM: a python pipeline for Modelica based district and urban scale energy simulations

ABSTRACT

Energy simulation models are crucial to estimate the energy demand of buildings, especially for prospective planning on a district or city scale. As required input data is not available in many cases, an automated model generation workflow is needed. Existing workflows have several disadvantages, including: (i) dependence on large input datasets of existing buildings; (ii) no 3D representation to support the planning process; (iii) they are proprietary solutions. The pipeline ‘SHP2SIM’ is an open-source python pipeline enabling enrichment and generation of building energy simulation models based on little input data for district and urban scale. The pipeline is tested by simulating the heat load for a district with 27 buildings and validated for one building: R squared is 0.9825, CV(RMSE) is 22.10%, and NMBE is 4.06% on a monthly basis. To enable reproducibility and encourage open science, input data, output models, and the pipeline are openly available (https://github.com/tug-cps/shp2sim).

KEYWORDS:

• Building energy simulation
• data enrichment
• Modelica model
• district scale
• urban scale

Acknowledgements

The reported research has been conducted within the project KityVR (879419), which has received funding in the framework of ‘Stadt der Zukunft’, a research and technology programme of the Austrian Ministry for Transport, Innovation and Technology (BMVIT). Supported by TU Graz Open Access Publishing Fund. The authors acknowledge the support by the University of Graz, Institute of Environmental System Sciences.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Austrian Ministry for Transport, Innovation and Technology [879419]; TU Graz Open Access Publishing Fund.