Wien Energie: Optimizing cooling networks based on setpoints from Gradyent’s Digital Twin

Wien Energie operates eight 25 district cooling centers in Vienna, of which eight are connected to networks and 17 are local. The total capacity is 240 MW. The energy provider is looking to expand its cooling capacity to 370 MW until 2030 and become “Europe’s district cooling capital.”

Wien Energie has used Gradyent’s Digital Twin Platform in the district heating system since 2020, reducing heat losses, CO₂ emissions, and operating costs. Drawing on Gradyent’s expertise, Wien Energie seeks to further improve its cooling system using modeling.

Challenge 

Wien Energie faced a complex setup for chilled water production, involving multiple compression chillers of different types at a single site alongside decentralized heat pumps. Managing this diverse infrastructure efficiently poses significant operational challenges. Furthermore, any intervention in the running system has to integrate seamlessly with the existing SCADA system used for controlling cold production cooling networks.

Solution 

Gradyent’s team developed an optimization strategy with estimation-based control and prepared to go live with setpoints designed to maximize chiller efficiency using the Digital Twin Platform.

Gradyent's Digital Twin creates a digital copy of the entire network that runs in real time, combining geographical, weather, and sensor data with physics-based models and AI. The Digital Twin provides insights into the entire system – even for places where no data or smart meters were available.

The go-live process was carried out in two phases to validate the setpoints within the client’s system. The efficiency in the operation of Wien Energie’s cooling systems has been improved based on the setpoints provided by the Digital Twin.

Results 

Source optimization was achieved using an energy demand forecast, enabling the Digital Twin to select the most efficient combination of compression chillers to meet chilled water requirements.

The delivered forecast ensures compliance with all operational constraints, including minimum runtimes and ramp-up times of the chillers. This resulted in the creation of an accurate network model and individual models for each compression chiller; all integrated into the Digital Twin.

The implementation of setpoints for controlling Wien Energie’s compression chillers took place over two test runs, during which the setpoints were evaluated for operational validity. The data collected during these periods was used to enhance the robustness of the optimization strategy.

Since the test periods ended, the setpoints are automatically integrated into Wien Energie’s SCADA system and implemented in the machines. Wien Energie now optimizes chilled water production in real time with the support of Gradyent’s Digital Twin.