In the energy transition context, district heating have great potential for generating low-carbon and cost-effective heat. They can also provide flexibility to the electrical system thanks to sector coupling solutions and thermal energy storage allowing, for instance, better integration of intermittent renewable energy sources. Therefore, assessing the competitiveness of district heating would require a sector-coupled optimisation model with, as an input parameter, the costs of the district heating infrastructure estimated throughout the entire territory (a geographic zone of a given size) at a high spatial resolution, gathered in ready-to-implement clusters. Building on the work from Persson and Werner, we present a methodology to map and cluster district heating network costs on an entire territory. It relies on easy-to-access geospatial key variables such as heat demand, building density and winter temperatures. As a case study, we apply it to France and design two clustering approaches to gather the infrastructure costs: competitiveness-based and territory typology-based – to satisfy different model architectures. We observe, for instance, a 51 TWh annual heat supply potential for district heating in French urban areas for a total investment of 10 b€. With this comprehensive and replicable methodology, we aim to pave the way for a new and more accurate competitiveness assessment of district heating in sector-coupled models.
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Hofmann et al. (2025) studied this question.
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