Modeling with the 223P Ontology and Adaptation for Optimized DHC Operation

District heating and cooling (DHC) offers great potential for efficient, cost-effective and flexible large-scale use of low-carbon energy in the building sector. However reaching Net Zero Emissions by 2050 requires significant efforts to rapidly improve the energy efficiency of existing networks, switch them to renewable heat sources, integrate secondary heat sources and to develop new high-efficiency infrastructure. A critical factor for reaching these goals is the digitalization of these systems to access new tools like the identification of problematic consumer substations, predictive maintenance, optimized heat production, evaluation of potential extensions and efficient sector coupling. This paper proposes an extension of the emerging ASHRAE 223P standard for machine-readable semantic frameworks representing building automation and control data, and other building system information to DHC networks. it is validated through two use cases in two distinct research projects. The adapted 223P ontology could be a starting point for the development of a standard data model of DHC networks.