https://doi.org/10.1051/epjconf/202532307002
Unscented Kalman Filtering for in-situ Bulk Identification of District Heating Meter Temperature Offsets and Service Pipe Insulation Level Detection
1 Danish Technological Institute, Energy and Climate, Kongsvang Allé 29, 8000 Aarhus, Denmark
2 VSL National Metrology Institute, Thijsseweg 11, 2629 JA Delft, Netherlands
* Corresponding author: peo@teknologisk.dk
Published online: 7 April 2025
Unscented Kalman Filtering is applied to district heating meter data and GIS-data from a utility network to simultaneously identify temperature offsets in utility meters and service pipe insulation. Implementing estimation of the temperature in the main pipe allows for more accurate results, which also respect physical constraints. Unscented Transformations allow for easier implementation of the algorithm compared to existing solutions, as linearization is avoided. Correcting for potential offsets in the temperature measurement of the utility meter allows for a better estimation of the insulation level of the service pipe, improving the ability for the utilities to pinpoint their efforts in optimizing their renovation activities over several areas of interest.
Publisher note: The PDF of this article has been revised to include the following acknowledgements: “The project (22DIT02 FunSNM) has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.”, on May 14, 2025.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
