维护可持续区域供热系统的智能方法:技术、挑战和未来方向

Parham Barzegaran Hosseini , Mousa Mohammadpourfard , Gülden Gökçen Akkurt , Mostafa Mohammadpourfard
{"title":"维护可持续区域供热系统的智能方法:技术、挑战和未来方向","authors":"Parham Barzegaran Hosseini ,&nbsp;Mousa Mohammadpourfard ,&nbsp;Gülden Gökçen Akkurt ,&nbsp;Mostafa Mohammadpourfard","doi":"10.1016/j.meaene.2025.100064","DOIUrl":null,"url":null,"abstract":"<div><div>Currently, district heating systems are essential for the effective distribution of energy derived from renewable sources, such as geothermal and solar thermal energy, to extensive regions, including residential and urban communities. However, faults can affect the system's efficiency and lead to energy waste and significant economic losses. DHS's dependability and effectiveness are even more important as the shift to renewable energy sources accelerates, especially under the Net Zero Emissions by 2025 Scenario. Leakage can be one of the critical faults in the system, including the loss of energy, impact on the environment, challenging stability, and damage to the system equipment. Therefore, leak detection must be quick and precise to avoid system issues and costs. This review study provides a comprehensive review of leakage detection methods, highlighting their evolution, advantages, limitations, and prospects. Traditional model-based approaches are analyzed alongside data-driven techniques and advanced methods such as Unmanned Airborne Infrared Thermography (UAIT). The review also discusses challenges like network complexity, sensor limitations, and the trade-offs between cost, accuracy, and efficiency of different methods. While many studies demonstrate promising results, their reliance on simulated data rather than real-world validation remains a key constraint. The article recommends integrating multiple methods to improve system monitoring and predictive maintenance. It also highlights future directions involving proposed algorithms and models based on state-space nonlinear methods, which are well-suited for complex systems such as DHS. This approach will be helpful in achieving high accuracy and faster detection within system. A view is held regarding the potential for improving the monitoring and predictive maintenance system while considering the sustainable use of renewable energies for district heating and discussing the benefits and drawbacks of those various detection methodologies.</div></div>","PeriodicalId":100897,"journal":{"name":"Measurement: Energy","volume":"8 ","pages":"Article 100064"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A smart approach to maintenance of sustainable district heating systems: Techniques, challenges, and future directions\",\"authors\":\"Parham Barzegaran Hosseini ,&nbsp;Mousa Mohammadpourfard ,&nbsp;Gülden Gökçen Akkurt ,&nbsp;Mostafa Mohammadpourfard\",\"doi\":\"10.1016/j.meaene.2025.100064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Currently, district heating systems are essential for the effective distribution of energy derived from renewable sources, such as geothermal and solar thermal energy, to extensive regions, including residential and urban communities. However, faults can affect the system's efficiency and lead to energy waste and significant economic losses. DHS's dependability and effectiveness are even more important as the shift to renewable energy sources accelerates, especially under the Net Zero Emissions by 2025 Scenario. Leakage can be one of the critical faults in the system, including the loss of energy, impact on the environment, challenging stability, and damage to the system equipment. Therefore, leak detection must be quick and precise to avoid system issues and costs. This review study provides a comprehensive review of leakage detection methods, highlighting their evolution, advantages, limitations, and prospects. Traditional model-based approaches are analyzed alongside data-driven techniques and advanced methods such as Unmanned Airborne Infrared Thermography (UAIT). The review also discusses challenges like network complexity, sensor limitations, and the trade-offs between cost, accuracy, and efficiency of different methods. While many studies demonstrate promising results, their reliance on simulated data rather than real-world validation remains a key constraint. The article recommends integrating multiple methods to improve system monitoring and predictive maintenance. It also highlights future directions involving proposed algorithms and models based on state-space nonlinear methods, which are well-suited for complex systems such as DHS. This approach will be helpful in achieving high accuracy and faster detection within system. A view is held regarding the potential for improving the monitoring and predictive maintenance system while considering the sustainable use of renewable energies for district heating and discussing the benefits and drawbacks of those various detection methodologies.</div></div>\",\"PeriodicalId\":100897,\"journal\":{\"name\":\"Measurement: Energy\",\"volume\":\"8 \",\"pages\":\"Article 100064\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Measurement: Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2950345025000314\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement: Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950345025000314","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目前,区域供热系统对于有效地向广大地区,包括住宅和城市社区分配来自可再生能源的能源,如地热和太阳热能,是必不可少的。但是,故障会影响系统的运行效率,造成能源的浪费和巨大的经济损失。随着向可再生能源转型的加速,特别是在2025年净零排放的情况下,国土安全部的可靠性和有效性变得更加重要。泄漏可能是系统中的关键故障之一,包括能量损失,对环境的影响,挑战稳定性以及对系统设备的损坏。因此,泄漏检测必须快速和精确,以避免系统问题和成本。本文对泄漏检测方法进行了综述,重点介绍了它们的发展、优势、局限性和前景。传统的基于模型的方法与数据驱动技术和先进的方法(如无人机机载红外热像仪(UAIT))一起进行了分析。该综述还讨论了网络复杂性、传感器限制以及不同方法的成本、准确性和效率之间的权衡等挑战。虽然许多研究显示出有希望的结果,但他们对模拟数据的依赖而不是现实世界的验证仍然是一个关键的限制。本文建议集成多种方法来改进系统监控和预测性维护。它还强调了未来的方向,涉及基于状态空间非线性方法的算法和模型,这些方法非常适合于复杂的系统,如DHS。该方法将有助于实现系统内的高精度和快速检测。在考虑可持续地利用可再生能源进行区域供热的同时,对改进监测和预测性维护系统的潜力提出了看法,并讨论了这些不同检测方法的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A smart approach to maintenance of sustainable district heating systems: Techniques, challenges, and future directions

A smart approach to maintenance of sustainable district heating systems: Techniques, challenges, and future directions
Currently, district heating systems are essential for the effective distribution of energy derived from renewable sources, such as geothermal and solar thermal energy, to extensive regions, including residential and urban communities. However, faults can affect the system's efficiency and lead to energy waste and significant economic losses. DHS's dependability and effectiveness are even more important as the shift to renewable energy sources accelerates, especially under the Net Zero Emissions by 2025 Scenario. Leakage can be one of the critical faults in the system, including the loss of energy, impact on the environment, challenging stability, and damage to the system equipment. Therefore, leak detection must be quick and precise to avoid system issues and costs. This review study provides a comprehensive review of leakage detection methods, highlighting their evolution, advantages, limitations, and prospects. Traditional model-based approaches are analyzed alongside data-driven techniques and advanced methods such as Unmanned Airborne Infrared Thermography (UAIT). The review also discusses challenges like network complexity, sensor limitations, and the trade-offs between cost, accuracy, and efficiency of different methods. While many studies demonstrate promising results, their reliance on simulated data rather than real-world validation remains a key constraint. The article recommends integrating multiple methods to improve system monitoring and predictive maintenance. It also highlights future directions involving proposed algorithms and models based on state-space nonlinear methods, which are well-suited for complex systems such as DHS. This approach will be helpful in achieving high accuracy and faster detection within system. A view is held regarding the potential for improving the monitoring and predictive maintenance system while considering the sustainable use of renewable energies for district heating and discussing the benefits and drawbacks of those various detection methodologies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信