GIS-based workflow for identifying renewable heat potentials and an optimal strategy for LowEx district heating

Abstract

To reach climate protection goals, Germany aims to significantly reduce emissions through the heat transition. Providing renewable heat sources in urban areas presents one of the greatest challenges due to the limited space, yet high energy demand. This thesis addresses the issue by creating a workflow based on GIS (Geographic Information Systems) to quickly identify socalled “sub-areas” where low temperature (LowEx) district heating could be suitable. The heating concept shall connect sources of shallow geothermal energy within an observed area and enable a more effective distribution of heat. Photovoltaics (PV) on roofs as well as parking lots shall counter the increased power demand of the decentralized heat pumps. The workflow involves estimations of annual technical potentials and the identification of sub-areas using ArcGIS Pro, Polysun, and Earth Energy Designer. This was created based on and applied to the district of Neu-Schwachhausen. Bremen. Scenarios (S) of 2022, 2030, 2038-a, and 2038-b were observed, varying the availability of the selected technologies (borehole heat exchanger and PV) and the level of heat demand for space and water heating. The sub-areas were evaluated regarding overall quality based on selected criteria. Results show that such a concept of LowEx DH is the ideal heating strategy for the district if the circumstances in S-2038-b can be achieved. Most neighborhoods would be technically suitable, especially due to the 300 m deep boreholes and heat demand reductions. Considering the cumulated values, the required power for heat pumps could be covered by PV alone in many of the areas, underlining the necessity of efficient energy storage in reality. Solar parking lots have a less substantial impact overall compared to roof potentials, though a detailed feasibility study is recommended to confirm this. This thesis also shows the importance of sharing local sources between neighborhoods, in addition to using large sports fields, to efficiently maximize area usage. Prioritizing these elements would lead to higher energy self-sufficiency in the subareas. In further research, the workflow can be extended by adding an economic parameter, seasonal fluctuations, and improved automation.