Data-Driven Design and optimization of future 4GDH networks

The economic strength of future heat networks lies in the ability to cover the heat demand and secure the expected comfort for the end-users with an average supply and return temperature of 55/25 °C and the flexibility to increase the supply to no more than 70 °C only during very cold spells during wintertime. The project's main goal is to demonstrate innovative data-driven services that can improve current outdated design procedures and parameters to optimize the magnitude of design heat demand, the sizing of systems and components, and the future hydraulic operating conditions under low supply and return temperatures. The technical challenges require a multidisciplinary approach combining engineering skills regarding thermo-fluid dynamics with data science and statistical approaches, integrating high-resolution energy meter data, clustering of DH customers, and probability distribution of simultaneity of heating demand.