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A diagnostic approach for fault detection and identification in district heating networks

Author

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  • Manservigi, Lucrezia
  • Bahlawan, Hilal
  • Losi, Enzo
  • Morini, Mirko
  • Spina, Pier Ruggero
  • Venturini, Mauro

Abstract

District Heating Network (DHN) pipes can be affected by faults that endanger system reliability. Thus, this paper develops a novel modeling and diagnostic approach for the detection and identification of the most frequent faults that affect DHN pipes, i.e., water leakages, heat losses and pressure losses.

Suggested Citation

  • Manservigi, Lucrezia & Bahlawan, Hilal & Losi, Enzo & Morini, Mirko & Spina, Pier Ruggero & Venturini, Mauro, 2022. "A diagnostic approach for fault detection and identification in district heating networks," Energy, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:energy:v:251:y:2022:i:c:s036054422200891x
    DOI: 10.1016/j.energy.2022.123988
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    References listed on IDEAS

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    1. Stanislav Chicherin & Vladislav Mašatin & Andres Siirde & Anna Volkova, 2020. "Method for Assessing Heat Loss in A District Heating Network with A Focus on the State of Insulation and Actual Demand for Useful Energy," Energies, MDPI, vol. 13(17), pages 1-15, September.
    2. Badami, Marco & Fonti, Antonio & Carpignano, Andrea & Grosso, Daniele, 2018. "Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach," Energy, Elsevier, vol. 144(C), pages 826-838.
    3. Pipiciello, Mauro & Caldera, Matteo & Cozzini, Marco & Ancona, Maria A. & Melino, Francesco & Di Pietra, Biagio, 2021. "Experimental characterization of a prototype of bidirectional substation for district heating with thermal prosumers," Energy, Elsevier, vol. 223(C).
    4. Ürge-Vorsatz, Diana & Cabeza, Luisa F. & Serrano, Susana & Barreneche, Camila & Petrichenko, Ksenia, 2015. "Heating and cooling energy trends and drivers in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 85-98.
    5. Marguerite, C. & Andresen, G.B. & Dahl, M., 2018. "Multi-criteria analysis of storages integration and operation solutions into the district heating network of Aarhus – A simulation case study," Energy, Elsevier, vol. 158(C), pages 81-88.
    6. Ocłoń, Paweł & Nowak-Ocłoń, Marzena & Vallati, Andrea & Quintino, Alessandro & Corcione, Massimo, 2019. "Numerical determination of temperature distribution in heating network," Energy, Elsevier, vol. 183(C), pages 880-891.
    7. Ozgener, Leyla & Ozgener, Onder, 2009. "Monitoring of energy exergy efficiencies and exergoeconomic parameters of geothermal district heating systems (GDHSs)," Applied Energy, Elsevier, vol. 86(9), pages 1704-1711, September.
    8. Marty, Fabien & Serra, Sylvain & Sochard, Sabine & Reneaume, Jean-Michel, 2018. "Simultaneous optimization of the district heating network topology and the Organic Rankine Cycle sizing of a geothermal plant," Energy, Elsevier, vol. 159(C), pages 1060-1074.
    9. Rimkevicius, Sigitas & Kaliatka, Algirdas & Valincius, Mindaugas & Dundulis, Gintautas & Janulionis, Remigijus & Grybenas, Albertas & Zutautaite, Inga, 2012. "Development of approach for reliability assessment of pipeline network systems," Applied Energy, Elsevier, vol. 94(C), pages 22-33.
    10. Guelpa, Elisa & Sciacovelli, Adriano & Verda, Vittorio, 2019. "Thermo-fluid dynamic model of large district heating networks for the analysis of primary energy savings," Energy, Elsevier, vol. 184(C), pages 34-44.
    11. Suryanarayana, Gowri & Lago, Jesus & Geysen, Davy & Aleksiejuk, Piotr & Johansson, Christian, 2018. "Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods," Energy, Elsevier, vol. 157(C), pages 141-149.
    12. Peter Lidén & Bijan Adl-Zarrabi & Carl-Eric Hagentoft, 2021. "Diagnostic Protocol for Thermal Performance of District Heating Pipes in Operation. Part 2: Estimation of Present Thermal Conductivity in Aged Pipe Insulation," Energies, MDPI, vol. 14(17), pages 1-15, August.
    13. Månsson, Sara & Johansson Kallioniemi, Per-Olof & Thern, Marcus & Van Oevelen, Tijs & Sernhed, Kerstin, 2019. "Faults in district heating customer installations and ways to approach them: Experiences from Swedish utilities," Energy, Elsevier, vol. 180(C), pages 163-174.
    14. De Lorenzi, Andrea & Gambarotta, Agostino & Morini, Mirko & Rossi, Michele & Saletti, Costanza, 2020. "Setup and testing of smart controllers for small-scale district heating networks: An integrated framework," Energy, Elsevier, vol. 205(C).
    15. Kurek, Teresa & Bielecki, Artur & Świrski, Konrad & Wojdan, Konrad & Guzek, Michał & Białek, Jakub & Brzozowski, Rafał & Serafin, Rafał, 2021. "Heat demand forecasting algorithm for a Warsaw district heating network," Energy, Elsevier, vol. 217(C).
    16. Zheng, Xuejing & Sun, Qihang & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & You, Shijun & Zhang, Huan & Shi, Kaiyu, 2021. "Thermo-hydraulic coupled simulation and analysis of a real large-scale complex district heating network in Tianjin," Energy, Elsevier, vol. 236(C).
    17. Hering, Dominik & Cansev, Mehmet Ege & Tamassia, Eugenio & Xhonneux, André & Müller, Dirk, 2021. "Temperature control of a low-temperature district heating network with Model Predictive Control and Mixed-Integer Quadratically Constrained Programming," Energy, Elsevier, vol. 224(C).
    18. Danielewicz, J. & Śniechowska, B. & Sayegh, M.A. & Fidorów, N. & Jouhara, H., 2016. "Three-dimensional numerical model of heat losses from district heating network pre-insulated pipes buried in the ground," Energy, Elsevier, vol. 108(C), pages 172-184.
    19. Guelpa, Elisa & Toro, Claudia & Sciacovelli, Adriano & Melli, Roberto & Sciubba, Enrico & Verda, Vittorio, 2016. "Optimal operation of large district heating networks through fast fluid-dynamic simulation," Energy, Elsevier, vol. 102(C), pages 586-595.
    20. Jebamalai, Joseph Maria & Marlein, Kurt & Laverge, Jelle, 2020. "Influence of centralized and distributed thermal energy storage on district heating network design," Energy, Elsevier, vol. 202(C).
    21. Kaliatka, A. & Valinčius, M., 2012. "Modeling of pipe break accident in a district heating system using RELAP5 computer code," Energy, Elsevier, vol. 44(1), pages 813-819.
    22. Gross, Michel & Karbasi, Babak & Reiners, Tobias & Altieri, Lisa & Wagner, Hermann-Josef & Bertsch, Valentin, 2021. "Implementing prosumers into heating networks," Energy, Elsevier, vol. 230(C).
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    Cited by:

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    2. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zhu, Zhaozhe & Bai, He & Li, Qicheng & Zheng, Lijun & Gao, Xinyong & You, Shijun, 2023. "Difference analysis and recognition of hydraulic oscillation by two types of sudden faults on long-distance district heating pipeline," Energy, Elsevier, vol. 284(C).
    3. Fester, Jakob & Østergaard, Peter Friis & Bentsen, Fredrik & Nielsen, Brian Kongsgaard, 2023. "A data-driven method for heat loss estimation from district heating service pipes using heat meter- and GIS data," Energy, Elsevier, vol. 277(C).
    4. Dong, Zhe & Cheng, Zhonghua & Zhu, Yunlong & Zhang, Zuoyi & Dong, Yujie & Huang, Xiaojin, 2024. "Passivity-based control of fluid flow networks with capacitance," Energy, Elsevier, vol. 299(C).

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