ServiceUpdated on 12 September 2024
Predictive maintenance and real-time operation optimization for heat pump and refrigeration systems using cloud computing and digital twins
About
We have experience developing and implementing toolchains that reduce the impact of faults on the performance of heat pump and refrigeration systems using digital twin technology. This technology involves suitable and modular simulation models that are adjusted over time based on measurements. By coupling this technology with optimization algorithms and cloud computing, we can define optimal maintenance intervals and set point adjustments in real time for different levels of performance degradation. This has the potential to increase the energy efficiency of heat pump and refrigeration systems while reducing operation and maintenance costs.
Type
- Technology Partner
- R&D Partner
- Consultant
Similar opportunities
Project cooperation
- R&D Partner
Arpad Török
researcher at Sesam Technology SRL Berceni
Romania
Project cooperation
- CM2025- 05: Hydrogen and renewable fuels
- CM2025- 07: Integrated regional energy systems
- CM2025- 08: Integrated industrial energy systems
- CM2025- 04: Carbon capture, utilisation and storage (CCUS)
- CM2025- 06: Call Module 2025-06: Heating and cooling technologies
- CM2025- 03: Advanced renewable energy (RE) technologies for power production
- CM2025-02: Energy system flexibility: renewables production, storage and system integration
- CM2025-01: Multi-vector interactions between the integrated energy system and industrial frameworks
Matthias Finkenrath
Professor for energy and process engineering at Kempten University of Applied Sciences
Kempten, Germany
Service
- Consultant
- R&D Partner
- Technology Partner
Haoshui Yu
Associate professor at Aalborg University
Denmark