Abstract
For district heating systems (DHS) to operate cost-effectively, avoid disturbances of loads, and increase overall energy efficiency, faults in DHSs must be detected, located, and rectified quickly. For this purpose, a novel digital twin-based fault detection and diagnosis framework with virtual sensor employment have been developed. The framework defines virtual sensors measuring the mass flow rate in points in the DHS where sensors are absent by using the existing sensors in the system. Faults in the virtual sensors are detected when deviations occur between the calculated and digital twin-simulated mass flow rate using a bound of normal operation, allowing some degree of modelling error. To define which virtual sensors are of interest, a novel Specialised Agglomerative Hierarchical Clustering algorithm will be used. A case study on a DHS of a suburb in Odense showed how the framework was able to locate faults with a top-down approach and could indicate whether the fault was local or due to upstream faults. The framework has the potential to be implemented in real-time monitoring of a DHS.
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Acknowledgements
This work is supported by the “Proactive and Predictive Maintenance of District Heating Systems” and “IEA DHC TS4”, funded by the Danish Energy Agency under the Energy Technology Development and Demonstration Program, ID number 64020-2102 and 134-22011, respectively. We also thank Peer Andersen, Lasse Elmelund Pedersen, and the rest of their team at Fjernvarme Fyn A/S for their assistance with the data and the model. Also, thanks to Johan Peter Alsing from Danfoss A/S for assisting us with Leanheat Network.
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Bank, T., Madsen, F.W., Mortensen, L.K., Søndergaard, H.A.N., Shaker, H.R. (2024). Virtual Sensor-Based Fault Detection and Diagnosis Framework for District Heating Systems: A Top-Down Approach for Quick Fault Localisation. In: Jørgensen, B.N., da Silva, L.C.P., Ma, Z. (eds) Energy Informatics. EI.A 2023. Lecture Notes in Computer Science, vol 14468. Springer, Cham. https://doi.org/10.1007/978-3-031-48652-4_19
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