Assessment of data integration and data links between urban building energy models and urban heat planning tools - A case study on a district in the city of Kiel with a focus on the demand side using MITs UBEM and the Hotmaps toolbox

Abstract

Heat provision for buildings notably contributes to global carbon dioxide emissions, especially in cities. Heat planning and simulations tools can help decision-makers to develop decarbonization roadmaps for the heating sector of their city. This motivates to conduct research in the field. Within the scope of the thesis two heat planning and simulation tools will be applied in a new integrated toolchain approach for the first time: The Hotmaps toolbox (development led by Technical University of Vienna (TUW)), and an Urban Building Energy Model (UBEM) (development led by Massachusetts Institute of Technology (MIT)). The integrated toolchain will consist of an UBEM on the demand side, as well as the Hotmaps toolbox on the supply side. The research question of the thesis aims to identify impacts of model calibrations on heat demands, reductions of carbon emissions, heating costs, and carbon abatement costs. Alongside the integrated toolchain, four sensitivity blocks (1. Initial refurbishment status; 2. Refurbishment options; 3. Allocation of heat demand to hectares; 4. Supply-side calibrations) impacts will be assessed. The case study shall help future users to create an understanding of the consequences and limitations of different approaches to calibrate their models. Applied methodologies, input data, and model calibrations will be described in detail through out the thesis. The new approach of an integrated toolchain will be identified as feasible. Different approaches to initial model calibration will lead to 13.61% deviation in heat demands from UBEMs. This will cause knock-on-effects for applicable refurbishment options: Reductions of heat demand between refurbished versions of the initial models will vary from 1.48 to 32.68% depending on the refurbishment measures being employed. Accordingly, different supply options will be considered optimal, leading to deviations in total costs over lifetime (up to 12.67%), carbon emissions (up to 24.64%), and carbon abatement costs (up to 119.87%). Hence, by the knock-on-effects along the toolchain, initial calibrations of UBEM (Sensitivity block 1) will have the greatest impact on results. In general, the earlier along the integrated toolchain a variation, the more significant its impact on results will be. Therefore, future users should pay utmost attention to the initial calibration of their UBEM and try to verify it with metered or available data before proceeding. In conclusion, considering its high spatial granularity of results and substantial efforts required in the process, the integrated toolchain will be identified as a preferential approach for heat planning, when high levels of detail are required and sufficient data, time, and expertise are available.