INDIGO, a 3 and a half year project, aims to develop a more efficient, intelligent and economical generation of District Cooling systems by improving system planning, control and management. This target will be achieved through the following specific objectives:

  • Contribute to the wider use of DC systems and motivate the competitiveness of European DC market by the development of two open-source tools:
    • A planning tool for DC systems with the aim of supporting their optimal design;
    • A library with thermo-fluid dynamic models of DC System components which will provide the designers detailed information about their physical behaviour.
  • Primary energy reduction addressed by a ground breaking DC system management strategy focused mainly on energy efficiency maximization but also on energy cost minimization. Its main characteristics is the predictive management but it also will address other challenges such as:
    • Integration of Renewable Energy Sources;
    • Dealing with different types of cooling sources;
    • Suitable coupling between generation, storage and demand.

All this, with the help of intelligent and innovative component controllers (Predictive Controllers) to be developed at all DC system levels. Some of them include embedded self-learning algorithms, allowing components to respond appropriately to the set-points established.

Developments carried out within INDIGO will be validated in a real District Heating and Cooling installation with appropriate conditions for testing the new functionalities.