IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v133y2015icp314-322.html
   My bibliography  Save this article

Integrated assessment of failure probability of the district heating network

Author

Listed:
  • ValinÄ ius, Mindaugas
  • ŽutautaitÄ—, Inga
  • Dundulis, Gintautas
  • RimkeviÄ ius, Sigitas
  • Janulionis, Remigijus
  • Bakas, Rimantas

Abstract

The aim of the research presented in this paper is the assessment of failure probability of the district heating network piping. The applied methodology for assessment of failure probability of the piping network energy systems includes three types of analyses: probabilistic mathematical, deterministic thermal-hydraulic and integrated deterministic–probabilistic structural integrity analyses. The analysis of Kaunas (Lithuania) district heating (DH) network was performed. First of all, the statistical analysis was performed and the piping with the highest failure rate was determined. The thermal-hydraulic analysis was performed and loads for deterministic–probabilistic structural analysis were calculated for the selected part of DH network. The integrated deterministic–probabilistic structural integrity analysis was performed in two steps—general structural integrity evaluation and probabilistic analysis of chosen piping part. Finally, the probabilistic mathematical method was applied for the integrated assessment of failure probability of the DH network piping. This method takes into consideration statistical information about Kaunas DH piping failure data, system structure, and pipe failure probability received by integrated deterministic–probabilistic structural integrity analysis.

Suggested Citation

  • ValinÄ ius, Mindaugas & ŽutautaitÄ—, Inga & Dundulis, Gintautas & RimkeviÄ ius, Sigitas & Janulionis, Remigijus & Bakas, Rimantas, 2015. "Integrated assessment of failure probability of the district heating network," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 314-322.
    • Handle: RePEc:eee:reensy:v:133:y:2015:i:c:p:314-322
    DOI: 10.1016/j.ress.2014.09.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832014002385
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2014.09.022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Maes, M.A. & Dann, M. & Salama, M.M., 2008. "Influence of grade on the reliability of corroding pipelines," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 447-455.
    2. Davis, P. & Burn, S. & Moglia, M. & Gould, S., 2007. "A physical probabilistic model to predict failure rates in buried PVC pipelines," Reliability Engineering and System Safety, Elsevier, vol. 92(9), pages 1258-1266.
    3. Sun, Yong & Ma, Lin & Morris, Jon, 2009. "A practical approach for reliability prediction of pipeline systems," European Journal of Operational Research, Elsevier, vol. 198(1), pages 210-214, October.
    4. Gerbec, Marko, 2010. "A reliability analysis of a natural-gas pressure-regulating installation," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1154-1163.
    5. 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.
    6. Kang, Won-Hee & Kliese, Alyce, 2014. "A rapid reliability estimation method for directed acyclic lifeline networks with statistically dependent components," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 81-91.
    7. Lauenburg, P. & Johansson, P.-O. & Wollerstrand, J., 2010. "District heating in case of power failure," Applied Energy, Elsevier, vol. 87(4), pages 1176-1186, April.
    8. Najafi, Massieh & Auslander, David M. & Bartlett, Peter L. & Haves, Philip & Sohn, Michael D., 2012. "Application of machine learning in the fault diagnostics of air handling units," Applied Energy, Elsevier, vol. 96(C), pages 347-358.
    9. Yan, Aibin & Zhao, Jun & An, Qingsong & Zhao, Yulong & Li, Hailong & Huang, Yrjö Jun, 2013. "Hydraulic performance of a new district heating systems with distributed variable speed pumps," Applied Energy, Elsevier, vol. 112(C), pages 876-885.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Babiarz, Bożena & Blokus, Agnieszka, 2020. "Dependency of technological lines in reliability analysis of heat production," Energy, Elsevier, vol. 211(C).
    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. Shamshirband, Shahaboddin & Petković, Dalibor & Enayatifar, Rasul & Hanan Abdullah, Abdul & Marković, Dušan & Lee, Malrey & Ahmad, Rodina, 2015. "Heat load prediction in district heating systems with adaptive neuro-fuzzy method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 760-767.
    4. Bistouni, Fathollah & Jahanshahi, Mohsen, 2015. "Evaluating failure rate of fault-tolerant multistage interconnection networks using Weibull life distribution," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 128-146.
    5. Michael-Allan Millar & Neil M. Burnside & Zhibin Yu, 2019. "District Heating Challenges for the UK," Energies, MDPI, vol. 12(2), pages 1-21, January.
    6. Guelpa, Elisa & Verda, Vittorio, 2018. "Model for optimal malfunction management in extended district heating networks," Applied Energy, Elsevier, vol. 230(C), pages 519-530.
    7. Shan, Xiaofang & Wang, Peng & Lu, Weizhen, 2017. "The reliability and availability evaluation of repairable district heating networks under changeable external conditions," Applied Energy, Elsevier, vol. 203(C), pages 686-695.
    8. Hast, Aira & Syri, Sanna & Lekavičius, Vidas & Galinis, Arvydas, 2018. "District heating in cities as a part of low-carbon energy system," Energy, Elsevier, vol. 152(C), pages 627-639.
    9. Dundulis, Gintautas & ŽutautaitÄ—, Inga & Janulionis, Remigijus & UÅ¡puras, Eugenijus & RimkeviÄ ius, Sigitas & Eid, Mohamed, 2016. "Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 195-202.
    10. Postnikov, Ivan & Stennikov, Valery & Mednikova, Ekaterina & Penkovskii, Andrey, 2018. "Methodology for optimization of component reliability of heat supply systems," Applied Energy, Elsevier, vol. 227(C), pages 365-374.
    11. Mortensen, Lasse Kappel & Shaker, Hamid Reza & Veje, Christian T., 2022. "Relative fault vulnerability prediction for energy distribution networks," Applied Energy, Elsevier, vol. 322(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohsin, R. & Majid, Z.A. & Yusof, M.Z., 2014. "Safety distance between underground natural gas and water pipeline facilities," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 53-60.
    2. Dundulis, Gintautas & ŽutautaitÄ—, Inga & Janulionis, Remigijus & UÅ¡puras, Eugenijus & RimkeviÄ ius, Sigitas & Eid, Mohamed, 2016. "Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 195-202.
    3. Xuejie Li & Yuan Xue & Yuxing Li & Qingshan Feng, 2022. "An Optimization Method for a Compressor Standby Scheme Based on Reliability Analysis," Energies, MDPI, vol. 15(21), pages 1-16, November.
    4. Mortensen, Lasse Kappel & Shaker, Hamid Reza & Veje, Christian T., 2022. "Relative fault vulnerability prediction for energy distribution networks," Applied Energy, Elsevier, vol. 322(C).
    5. Zhang, Xiaolei & Hu, Longhua & Delichatsios, Michael A. & Zhang, Jianping, 2019. "Experimental study on flame morphologic characteristics of wall attached non-premixed buoyancy driven turbulent flames," Applied Energy, Elsevier, vol. 254(C).
    6. Muniak, Damian Piotr, 2014. "A new methodology to determine the pre-setting of the control valve in a heating installation. A general model," Applied Energy, Elsevier, vol. 135(C), pages 35-42.
    7. Zheng, Jinfu & Zhou, Zhigang & Zhao, Jianing & Wang, Jinda, 2018. "Effects of the operation regulation modes of district heating system on an integrated heat and power dispatch system for wind power integration," Applied Energy, Elsevier, vol. 230(C), pages 1126-1139.
    8. Wang, Jie & Zhang, Yangyi & Li, Shunlong & Xu, Wencheng & Jin, Yao, 2024. "Directed network-based connectivity probability evaluation for urban bridges," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    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. Zhang, Lipeng & Gudmundsson, Oddgeir & Thorsen, Jan Eric & Li, Hongwei & Li, Xiaopeng & Svendsen, Svend, 2016. "Method for reducing excess heat supply experienced in typical Chinese district heating systems by achieving hydraulic balance and improving indoor air temperature control at the building level," Energy, Elsevier, vol. 107(C), pages 431-442.
    11. Liu, Zengkai & Liu, Yonghong & Zhang, Dawei & Cai, Baoping & Zheng, Chao, 2015. "Fault diagnosis for a solar assisted heat pump system under incomplete data and expert knowledge," Energy, Elsevier, vol. 87(C), pages 41-48.
    12. Zhou, Zhi-Jie & Hu, Chang-Hua & Xu, Dong-Ling & Chen, Mao-Yin & Zhou, Dong-Hua, 2010. "A model for real-time failure prognosis based on hidden Markov model and belief rule base," European Journal of Operational Research, Elsevier, vol. 207(1), pages 269-283, November.
    13. 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.
    14. Mohammad Taghi Tahooneh & Reza Dashti, 2022. "A new model for calculating rational failure rates based on network assets worth," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2221-2233, October.
    15. Bistouni, Fathollah & Jahanshahi, Mohsen, 2014. "Analyzing the reliability of shuffle-exchange networks using reliability block diagrams," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 97-106.
    16. Li, Jian & Dueñas-Osorio, Leonardo & Chen, Changkun & Shi, Congling, 2016. "Connectivity reliability and topological controllability of infrastructure networks: A comparative assessment," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 24-33.
    17. Lake, Andrew & Rezaie, Behanz & Beyerlein, Steven, 2017. "Review of district heating and cooling systems for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 417-425.
    18. Shan, Xiaofang & Wang, Peng & Lu, Weizhen, 2017. "The reliability and availability evaluation of repairable district heating networks under changeable external conditions," Applied Energy, Elsevier, vol. 203(C), pages 686-695.
    19. Kiluk, S., 2014. "Dynamic classification system in large-scale supervision of energy efficiency in buildings," Applied Energy, Elsevier, vol. 132(C), pages 1-14.
    20. Babiarz, Bożena & Blokus, Agnieszka, 2020. "Dependency of technological lines in reliability analysis of heat production," Energy, Elsevier, vol. 211(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:133:y:2015:i:c:p:314-322. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.