Towards automated fault detection and diagnosis in district heating customers: generation and analysis of a labeled dataset with ground truth

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Abstract

This study aims to develop a framework for automated fault detection and diagnosis (AFDD) in district heating (DH) substations by comprehensively understanding typical faults. AFDD is presently dependent on manual detection and diagnosis, leading to limitations. To address this issue, the study utilized data from 158 fault reports and smart heat meter data from residential buildings in Denmark to investigate common faults and conduct a fault impact assessment. The study suggests additional indicators for use by DH utility companies to detect anomalies in the future. The findings indicate that greater attention to fault detection and diagnosis can decrease energy usage and return temperatures, demonstrating the significance of AFDD implementation.
OriginalsprogEngelsk
TitelProceedings of Building Simulation 2023 : 18th Conference of International Building Performance Simulation Association. Shanghai, China, 4-6 September 2023
Antal sider8
Vol/bind18
ForlagInternational Building Performance Simulation Association
Publikationsdatosep. 2023
Sider3620-3628
Artikelnummer1576
ISBN (Elektronisk)978-1-7750520-3-6
DOI
StatusUdgivet - sep. 2023
BegivenhedIBPSA Building Simulation 2023 - Shanghai, Shanghai, Kina
Varighed: 4 sep. 20236 sep. 2023
https://bs2023.org/

Konference

KonferenceIBPSA Building Simulation 2023
LokationShanghai
Land/OmrådeKina
ByShanghai
Periode04/09/202306/09/2023
Internetadresse
NavnBuilding Simulation Conference proceedings
Vol/bind18
ISSN2522-2708

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