IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v284y2023ics036054422302090x.html
   My bibliography  Save this article

Difference analysis and recognition of hydraulic oscillation by two types of sudden faults on long-distance district heating pipeline

Author

Listed:
  • Yan, Jingjing
  • Zhang, Huan
  • Wang, Yaran
  • Zhu, Zhaozhe
  • Bai, He
  • Li, Qicheng
  • Zheng, Lijun
  • Gao, Xinyong
  • You, Shijun

Abstract

The implementation of long-distance district heating (LDH) systems, which rely on renewable energy sources, waste heat recovery, and waste heat reuse, offers a scientifically supported and environmentally friendly approach to achieving low-carbon emission reduction goals. As the common sudden failure on the long-distance district heating pipeline (LDHP), the leakage and valve failure will lead to strong hydraulic oscillation, which may cause heating failure if they are not recognized and handled in time. In this paper, the difference in hydraulic oscillation induced by leakage and valve failure is investigated with the hydraulic transient model. Based on the above analysis, a recognition method combining the support vector machine (SVM) and particle swarm optimization (PSO) is proposed to identify these two types of sudden faults. Taking a 20 km LDH system as an example, the effectiveness and robustness of the recognition method are investigated. The results show that the types, locations, and status of these two types of sudden faults can be accurately recognized and the robustness of the recognition method is strong when the sample time is less than 10 s. Our research deepens the understanding of the characteristics of the hydraulic oscillation induced by the leakage and valve failure on the LDHP and gives a new idea for the intelligent recognition of sudden faults online.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:284:y:2023:i:c:s036054422302090x
    DOI: 10.1016/j.energy.2023.128696
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422302090X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128696?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. Guelpa, Elisa & Verda, Vittorio, 2020. "Automatic fouling detection in district heating substations: Methodology and tests," Applied Energy, Elsevier, vol. 258(C).
    2. Neumayer, Martin & Stecher, Dominik & Grimm, Sebastian & Maier, Andreas & Bücker, Dominikus & Schmidt, Jochen, 2023. "Fault and anomaly detection in district heating substations: A survey on methodology and data sets," Energy, Elsevier, vol. 276(C).
    3. Liu, Zeyu & Li, Hang & Hou, Kai & Xu, Xiandong & Jia, Hongjie & Zhu, Lewei & Mu, Yunfei, 2023. "Risk assessment and alleviation of regional integrated energy system considering cross-system failures," Applied Energy, Elsevier, vol. 350(C).
    4. Lizana, Jesús & Ortiz, Carlos & Soltero, Víctor M. & Chacartegui, Ricardo, 2017. "District heating systems based on low-carbon energy technologies in Mediterranean areas," Energy, Elsevier, vol. 120(C), pages 397-416.
    5. Imen Harbaoui Dridi & Essia Ben Alaïa & Pierre Borne & Hanen Bouchriha, 2020. "Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 58(14), pages 4201-4214, July.
    6. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.
    7. Xu, Qian & Wang, Kang & Zou, Zhenwei & Zhong, Liqiong & Akkurt, Nevzat & Feng, Junxiao & Xiong, Yaxuan & Han, Jingxiao & Wang, Jiulong & Du, Yanping, 2021. "A new type of two-supply, one-return, triple pipe-structured heat loss model based on a low temperature district heating system," Energy, Elsevier, vol. 218(C).
    8. Sara Månsson & Kristin Davidsson & Patrick Lauenburg & Marcus Thern, 2018. "Automated Statistical Methods for Fault Detection in District Heating Customer Installations," Energies, MDPI, vol. 12(1), pages 1-18, December.
    9. Fang, Hao & Xia, Jianjun & Jiang, Yi, 2015. "Key issues and solutions in a district heating system using low-grade industrial waste heat," Energy, Elsevier, vol. 86(C), pages 589-602.
    10. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & You, Shijun, 2022. "Valve failure detection of the long-distance district heating pipeline by hydraulic oscillation recognition: A numerical approach," Energy, Elsevier, vol. 261(PA).
    11. Ziemele, Jelena & Gendelis, Stanislavs & Dace, Elina, 2023. "Impact of global warming and building renovation on the heat demand and district heating capacity: Case of the city of Riga," Energy, Elsevier, vol. 276(C).
    12. Li, Yemao & Xia, Jianjun & Su, Yingbo & Jiang, Yi, 2018. "Systematic optimization for the utilization of low-temperature industrial excess heat for district heating," Energy, Elsevier, vol. 144(C), pages 984-991.
    13. Liu, Yang & Xie, Xiaoqing & Wang, Mei, 2023. "Energy structure and carbon emission: Analysis against the background of the current energy crisis in the EU," Energy, Elsevier, vol. 280(C).
    14. Li, Yemao & Pan, Wenbiao & Xia, Jianjun & Jiang, Yi, 2019. "Combined heat and water system for long-distance heat transportation," Energy, Elsevier, vol. 172(C), pages 401-408.
    15. Sun, Fangtian & Fu, Lin & Sun, Jian & Zhang, Shigang, 2014. "A new waste heat district heating system with combined heat and power (CHP) based on ejector heat exchangers and absorption heat pumps," Energy, Elsevier, vol. 69(C), pages 516-524.
    16. 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).
    17. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    18. Zheng, Xuejing & Hu, Fangshu & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & Zhang, Huan & You, Shijun & Xu, Boxiao, 2021. "Leak detection of long-distance district heating pipeline: A hydraulic transient model-based approach," Energy, Elsevier, vol. 237(C).
    19. Gadd, Henrik & Werner, Sven, 2015. "Fault detection in district heating substations," Applied Energy, Elsevier, vol. 157(C), pages 51-59.
    20. Huo, Tengfei & Du, Qianxi & Xu, Linbo & Shi, Qingwei & Cong, Xiaobo & Cai, Weiguang, 2023. "Timetable and roadmap for achieving carbon peak and carbon neutrality of China's building sector," Energy, Elsevier, vol. 274(C).
    21. Liang, Weikun & Lin, Shunjiang & Liu, Mingbo & Sheng, Xuan & Pan, Yue & Liu, Yun, 2023. "Risk assessment for cascading failures in regional integrated energy system considering the pipeline dynamics," Energy, Elsevier, vol. 270(C).
    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. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zhu, Zhaozhe & Bai, He & Li, Qicheng & You, Shijun, 2024. "Pump-stopping-induced hydraulic oscillations in long-distance district heating system: Modelling and a comprehensive analysis of critical factors," Energy, Elsevier, vol. 294(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. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zhu, Zhaozhe & Bai, He & Li, Qicheng & You, Shijun, 2024. "Pump-stopping-induced hydraulic oscillations in long-distance district heating system: Modelling and a comprehensive analysis of critical factors," Energy, Elsevier, vol. 294(C).
    2. 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.
    3. Guelpa, Elisa & Verda, Vittorio, 2020. "Automatic fouling detection in district heating substations: Methodology and tests," Applied Energy, Elsevier, vol. 258(C).
    4. 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).
    5. Østergaard, Dorte Skaarup & Smith, Kevin Michael & Tunzi, Michele & Svendsen, Svend, 2022. "Low-temperature operation of heating systems to enable 4th generation district heating: A review," Energy, Elsevier, vol. 248(C).
    6. Li, Yu & Rezgui, Yacine & Zhu, Hanxing, 2017. "District heating and cooling optimization and enhancement – Towards integration of renewables, storage and smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 281-294.
    7. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Guelpa, Elisa & Marincioni, Ludovica, 2019. "Demand side management in district heating systems by innovative control," Energy, Elsevier, vol. 188(C).
    9. Kim, Ryunhee & Hong, Yejin & Choi, Youngwoong & Yoon, Sungmin, 2021. "System-level fouling detection of district heating substations using virtual-sensor-assisted building automation system," Energy, Elsevier, vol. 227(C).
    10. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zheng, Lijun & Gao, Xinyong & You, Shijun, 2022. "Valve failure detection of the long-distance district heating pipeline by hydraulic oscillation recognition: A numerical approach," Energy, Elsevier, vol. 261(PA).
    11. Neumayer, Martin & Stecher, Dominik & Grimm, Sebastian & Maier, Andreas & Bücker, Dominikus & Schmidt, Jochen, 2023. "Fault and anomaly detection in district heating substations: A survey on methodology and data sets," Energy, Elsevier, vol. 276(C).
    12. Sara Månsson & Kristin Davidsson & Patrick Lauenburg & Marcus Thern, 2018. "Automated Statistical Methods for Fault Detection in District Heating Customer Installations," Energies, MDPI, vol. 12(1), pages 1-18, December.
    13. Wang, Jingyi & Wang, Zhe & Zhou, Ding & Sun, Kaiyu, 2019. "Key issues and novel optimization approaches of industrial waste heat recovery in district heating systems," Energy, Elsevier, vol. 188(C).
    14. 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.
    15. Yang, Xiaolin & Kong, Ying & Zhou, Yu & Liu, Dawei & Xia, Jianjun, 2024. "Case study on combined heat and water system for district heating in Beijing through recovery of industrial waste heat in Tangshan," Energy, Elsevier, vol. 300(C).
    16. Guelpa, E. & Capone, M. & Sciacovelli, A. & Vasset, N. & Baviere, R. & Verda, V., 2023. "Reduction of supply temperature in existing district heating: A review of strategies and implementations," Energy, Elsevier, vol. 262(PB).
    17. Sun, Chunhua & Zhang, Haixiang & Cao, Shanshan & Xia, Guoqiang & Zhong, Jian & Wu, Xiangdong, 2023. "A hierarchical classifying and two-step training strategy for detection and diagnosis of anormal temperature in district heating system," Applied Energy, Elsevier, vol. 349(C).
    18. Alessandro Guzzini & Marco Pellegrini & Edoardo Pelliconi & Cesare Saccani, 2020. "Low Temperature District Heating: An Expert Opinion Survey," Energies, MDPI, vol. 13(4), pages 1-34, February.
    19. Sun, Fangtian & Chen, Xu & Fu, Lin & Zhang, Shigang, 2018. "Configuration optimization of an enhanced ejector heat exchanger based on an ejector refrigerator and a plate heat exchanger," Energy, Elsevier, vol. 164(C), pages 408-417.
    20. Shahrooz Abghari & Veselka Boeva & Jens Brage & Håkan Grahn, 2020. "A Higher Order Mining Approach for the Analysis of Real-World Datasets," Energies, MDPI, vol. 13(21), pages 1-23, November.

    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:energy:v:284:y:2023:i:c:s036054422302090x. 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: http://www.journals.elsevier.com/energy .

    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.