INDIGO – New generation of Intelligent Efficient District Cooling systems
The project specific objectives were:
- To contribute to a wider use of DC systems and motivate the competitiveness of European DC market by the development of two open-source tools for planning and simulation.
- A primary energy reduction over 45% addressed by a ground-breaking DC system management strategy. INDIGO solution achieves reductions in DC primary energy consumption compared to current systems thanks to improvements at different levels:
- At building level by anticipating the building needs, the consumer optimizes its cooling needs, reaching energy savings that can be as high as 62%
- At distribution level INDIGO cooling losses can be reduced up to 45% increasing at the same time the distribution temperature difference leading to further savings in the generation equipment.
- Optimal operation of the generation systems due to a suitable coupling between generation, storage and demand leads to additional energy savings that can be up to 50%.
A new management strategy has been developed that maximizes the overall DC efficiency or minimizes the running cost. One of its main characteristics is the predictive management, it integrates consumer demand and energy price forecasts and knowledge from fine-tuned models of DC system components. The manager controller optimizes setpoints for lower control layer and integrates a real-time feedback controller. Predictive Controllers have been developed for Buildings and Generation systems including embedded self-learning algorithms. Additional challenges addressed by the management strategy are the integration of renewable energy sources and different types of cooling sources. Additionally, two open tools have been developed to contribute to a wider use of DC systems: • An open-source planning tool for the evaluation/designing of existing/new DC systems • A specific open-source library with parametric thermo-fluid dynamic models of DC System components for design/analysis.