Unscented Kalman Filtering for in-situ Bulk Identification of District Heating Meter Temperature Offsets and Service Pipe Insulation Level Detection
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 a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2025/08/epjconf_cim2025_07002.pdf |
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| Summary: | 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. |
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| ISSN: | 2100-014X |