Identification of district heating and cooling system archetypes: a novel approach applied to a case study in Switzerland

District Heating and Cooling (DHC) systems are central to the decarbonisation of thermal energy supply. For efficient development and assessment of decarbonisation strategies amongst these diverse systems, it is essential to identify representative system archetypes that can serve as proxies for broader types in targeted case studies. Existing work often focuses on single-criteria and supply-side classifications, while overlooking demand-side diversity and the role of exergy in evaluating system performance. This study introduces a novel multi-criteria methodology for the demand-based characterisation and grouping of DHC districts, with exergy as a central metric. The method proposes four criteria to characterise supply regions on GIS-based data: exergy demand density (in place of traditional energy demand), degree of connection to reflect densification potential, and two building stock indicators reflecting ownership patterns and usage types to incorporate a social dimension. The methodology applies a K-medoids algorithm to group similar systems and identify representative archetypes within each group. To demonstrate the approach, it was applied to publicly available data on existing Swiss DHC systems. As the required data on supply regions was not readily available, it was first generated through a GIS-based analysis, using DBSCAN clustering to define district boundaries based on building-level information. This enabled the application of the proposed criteria and the identification of five distinct archetypes for Swiss DHC systems. Due to the slightly delayed perspective of the Swiss dataset, recent developments such as low-temperature networks are underrepresented while capturing the more established, higher-temperature networks where decarbonisation needs remain particularly significant.