Demonstration of digitization measures using the example of the Feldkirchen district heating network

Modern district heating systems are designed to combine heterogeneous energy sources and technologies such as renewables, waste heat, thermal storage, power grids, heat networks, and heat pumps.

The design process is both complicated and critical to the performance of the district heating network. In the DDM Feldkirchen project, a number of intelligent approaches (digital twin, model predictive controls, AI-based forecasts) are being developed not only to optimize the design of the networks, but also during their operation for

• an optimal control of the operational processes,
• accurate fault detection and
• control of transfer stations

is ensured. These approaches are being tested in the Feldkirchen heating network.

To support the transformation towards automated heating systems, model predictive control strategies incorporating AI-based predictive models are used that can compensate for changes in the grid as well as data failures, are robust to stochastic uncertainties, and are flexible and scalable.

• BC Regionalwärme Gruppe GmbH
• Hoval Gesellschaft m.b.H.
• GEF Ingenieur AG
• Energieagentur Obersteiermark GmbH
• Ingenieurbüro Jaindl & Garz GmbH
• Prozess Optimal CAP GmbH