Detection of heat carrier losses in centralized heating systems

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Дәйексөз келтіру

Толық мәтін

Аннотация

Centralized heating systems are widely used for providing heat to residential, commercial, and industrial buildings. However, one of the significant challenges in these systems is the loss of heat carrier (usually water or steam), which can lead to inefficiencies, increased operational costs, and environmental impacts. Detecting and addressing these losses is crucial for maintaining the efficiency and reliability of the heating system.

Авторлар туралы

Valeriy Grokhotov

Omsk State Technical University

Хат алмасуға жауапты Автор.
Email: 19valera94@mail.ru
SPIN-код: 9419-6170
ResearcherId: MCJ-1928-2025

Graduate Student, Senior Lecturer of the Heat Power Engineering Department

Ресей, Omsk

Andrey Mikhailov

Omsk State Technical University

Email: 19valera94@mail.ru
SPIN-код: 7337-8036
Scopus Author ID: 56503044200

Candidate of Technical Sciences, Associate Professor, Associate Professor of the Heat Power Engineering Department

Ресей, Omsk

Ivan Stepashkin

Omsk State Technical University

Email: 19valera94@mail.ru
SPIN-код: 3166-3378
Scopus Author ID: 57214754518

Senior Lecturer of the Heat Power Engineering Department

Ресей, Omsk

Әдебиет тізімі

  1. Otchet o sostoyanii teploenergetiki i tsentralizovannogo teplosnabzheniya v Rossiyskoy Federatsii v 2022 godu Ministry of Energy of the Russian Federation [Report on the state and district heating in the Russian Federation in 2022] // Minenergo Rossii. Ministry of Energy of Russian Federation. Moscow, 2023. 161 p. (In Russ.).
  2. Pochti tret’ teplosetey v Rossii nuzhdayetsya v zamene [Almost a third of heating networks in Russia need replacement] // RTVI. URL: https://rtvi.com/news/pochti-tret-teplosetej-v-rossii-nuzhdaetsya-v-zamene/ (accessed: 17.01.2025). (In Russ.).
  3. Dmitriyev V. Z. Sistemy tsentralizovannogo teplosnabzheniya goroda Omska i puti ikh sovershenstvovaniya [Omsk city district heating systems and ways to improve them]. Natsional’nyye prioritety Rossii. National Priorities of Russia. 2019. No. 4. P. 42–47. EDN: TQVEAQ. (In Russ.).
  4. El-Zahab S., Zayed T. Leak detection in water distribution networks: an introductory overview. Smart Water. 2019. Vol. 4 (1). doi: 10.1186/s40713-019-0017-x. (In Engl.).
  5. Shen Y., Chen J., Fu Q. [et al.]. Detection of district heating pipe network leakage fault using UCB arm selection method. Buildings. 2021. Vol. 11 (7). 275. doi: 10.3390/buildings11070275. (In Engl.).
  6. Örn Garðarsson G., Boem F., Toni L. Graph-Based Learning for Leak Detection and Localisation in Water Distribution Networks. IFAC-PapersOnLine. 2022. Vol. 55 (6). P. 661–666. doi: 10.1016/j.ifacol.2022.07.203. (In Engl.).
  7. Zhou S., Liu C., Zhao Y. Leakage diagnosis of heating pipe-network based on BP neural network. Sustainable Energy, Grids and Networks. 2022. Vol. 32. doi: 10.1016/j.segan.2022.100869. EDN: FJKAZY. (In Engl.).
  8. Van der Walt J. C., Heyns P. S., Wilke D. N. Pipe network leak detection: comparison between statistical and machine learning techniques. Urban Water Journal. 2018. Vol. 15 (10). doi: 10.1080/1573062X.2019.1597375. (In Engl.).
  9. Gosudarstvennyy doklad o sostoyanii energosberezheniya i povyshenii energeticheskoy effektivnosti v Rossiyskoy federatsii za 2022 god [State report on energy saving and efficiency in the Russian Federation in 2022] // Ministerstvo ekonomicheskogo razvitiya Rossiyskoy Federatsii. Ministry of Economic Development of the Russian Federation. URL: https://www.economy.gov.ru/material/file/b2ec92f00344707af95c8d44a6abbde8/Energy_efficiency_2023pdf (accessed: 12.11.2024). (In Russ.).
  10. Kosyakov S. I., Sadykov A. M., Sennikov V. V., Tikhonov A. I. Metod lokalizatsii mest utechek v teplovykh setyakh na osnove analiza dannykh uzlov ucheta potrebiteley teplovoy energii [Method of detection of district heating pipe network leakage using data monitoring of heat energy consumers]. Vestnik Ivanovskogo gosudarstvennogo energeticheskogo universiteta. Vestnik IGEU. 2021. No. 6. P. 70–78. doi: 10.17588/2072-2672.2021.6.070-078. EDN: IREILE. (In Russ.).

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