A Review of Intelligent Technologies in District Heating Systems

Zheng Grace Ma; Bo Nørregaard Jørgensen

doi:10.1007/978-3-031-73500-4_11

A Review of Intelligent Technologies in District Heating Systems

Zheng Grace Ma^*
, Bo Nørregaard Jørgensen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Intelligent technologies reshape district heating systems towards greater efficiency, cost-effectiveness, and sustainability. Addressing the challenges of their full implementation requires a clear understanding of the current research land-scape. This paper presents a scoping review of post-2000 literature from the Web of Science, focusing on the current state, emerging trends, and limitations of intelligent technologies for district heating systems. The review reveals a significant interest in machine learning for heat load prediction, operational efficiency, and fault detection, with an emerging focus on deep learning and hybrid models. However, research gaps remain, particularly in unsupervised learning, real-world case studies, and the integration of IoT and cloud computing, underscoring the need for further research. The result also shows the need for innovative solutions to enhance the resilience and adaptability of district heating systems within the rapidly evolving energy landscape.

Original language	English
Title of host publication	Progress in Artificial Intelligence : 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part II
Editors	Manuel Filipe Santos, José Machado, Paulo Novais, Paulo Cortez, Pedro Miguel Moreira
Publisher	Springer
Publication date	2025
Pages	123–134
ISBN (Print)	978-3-031-73499-1
ISBN (Electronic)	978-3-031-73500-4
DOIs	https://doi.org/10.1007/978-3-031-73500-4_11
Publication status	Published - 2025
Event	The EPIA Conference on Artificial Intelligence (AI) 2024 - Viana do Castelo, Portugal Duration: 3. Sept 2024 → 6. Sept 2024 https://epia2024.pt/

Conference

Conference	The EPIA Conference on Artificial Intelligence (AI) 2024
Country/Territory	Portugal
City	Viana do Castelo
Period	03/09/2024 → 06/09/2024
Internet address	https://epia2024.pt/

Series	Lecture Notes in Computer Science
Volume	14968
ISSN	0302-9743

Keywords

scoping review
district heating
artificial intelligence
digitalization
Scoping review

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10.1007/978-3-031-73500-4_11

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Ma, Z. G., & Jørgensen, B. N. (2025). A Review of Intelligent Technologies in District Heating Systems. In M. F. Santos, J. Machado, P. Novais, P. Cortez, & P. M. Moreira (Eds.), Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part II (pp. 123–134). Springer. https://doi.org/10.1007/978-3-031-73500-4_11

Ma, Zheng Grace ; Jørgensen, Bo Nørregaard. / A Review of Intelligent Technologies in District Heating Systems. Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part II. editor / Manuel Filipe Santos ; José Machado ; Paulo Novais ; Paulo Cortez ; Pedro Miguel Moreira. Springer, 2025. pp. 123–134 (Lecture Notes in Computer Science, Vol. 14968).

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title = "A Review of Intelligent Technologies in District Heating Systems",

abstract = "Intelligent technologies reshape district heating systems towards greater efficiency, cost-effectiveness, and sustainability. Addressing the challenges of their full implementation requires a clear understanding of the current research land-scape. This paper presents a scoping review of post-2000 literature from the Web of Science, focusing on the current state, emerging trends, and limitations of intelligent technologies for district heating systems. The review reveals a significant interest in machine learning for heat load prediction, operational efficiency, and fault detection, with an emerging focus on deep learning and hybrid models. However, research gaps remain, particularly in unsupervised learning, real-world case studies, and the integration of IoT and cloud computing, underscoring the need for further research. The result also shows the need for innovative solutions to enhance the resilience and adaptability of district heating systems within the rapidly evolving energy landscape.",

keywords = "scoping review, district heating, artificial intelligence, digitalization, Scoping review",

author = "Ma, \{Zheng Grace\} and J{\o}rgensen, \{Bo N{\o}rregaard\}",

year = "2025",

doi = "10.1007/978-3-031-73500-4\_11",

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isbn = "978-3-031-73499-1",

series = "Lecture Notes in Computer Science",

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editor = "Santos, \{Manuel Filipe\} and Jos{\'e} Machado and Paulo Novais and Paulo Cortez and Moreira, \{Pedro Miguel\}",

booktitle = "Progress in Artificial Intelligence",

address = "Germany",

note = "The EPIA Conference on Artificial Intelligence (AI) 2024, EPIA 2024 ; Conference date: 03-09-2024 Through 06-09-2024",

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Ma, ZG & Jørgensen, BN 2025, A Review of Intelligent Technologies in District Heating Systems. in MF Santos, J Machado, P Novais, P Cortez & PM Moreira (eds), Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part II. Springer, Lecture Notes in Computer Science, vol. 14968, pp. 123–134, The EPIA Conference on Artificial Intelligence (AI) 2024, Viana do Castelo, Portugal, 03/09/2024. https://doi.org/10.1007/978-3-031-73500-4_11

A Review of Intelligent Technologies in District Heating Systems. / Ma, Zheng Grace ; Jørgensen, Bo Nørregaard.
Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part II. ed. / Manuel Filipe Santos; José Machado; Paulo Novais; Paulo Cortez; Pedro Miguel Moreira. Springer, 2025. p. 123–134 (Lecture Notes in Computer Science, Vol. 14968).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Ma, Zheng Grace

AU - Jørgensen, Bo Nørregaard

PY - 2025

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N2 - Intelligent technologies reshape district heating systems towards greater efficiency, cost-effectiveness, and sustainability. Addressing the challenges of their full implementation requires a clear understanding of the current research land-scape. This paper presents a scoping review of post-2000 literature from the Web of Science, focusing on the current state, emerging trends, and limitations of intelligent technologies for district heating systems. The review reveals a significant interest in machine learning for heat load prediction, operational efficiency, and fault detection, with an emerging focus on deep learning and hybrid models. However, research gaps remain, particularly in unsupervised learning, real-world case studies, and the integration of IoT and cloud computing, underscoring the need for further research. The result also shows the need for innovative solutions to enhance the resilience and adaptability of district heating systems within the rapidly evolving energy landscape.

AB - Intelligent technologies reshape district heating systems towards greater efficiency, cost-effectiveness, and sustainability. Addressing the challenges of their full implementation requires a clear understanding of the current research land-scape. This paper presents a scoping review of post-2000 literature from the Web of Science, focusing on the current state, emerging trends, and limitations of intelligent technologies for district heating systems. The review reveals a significant interest in machine learning for heat load prediction, operational efficiency, and fault detection, with an emerging focus on deep learning and hybrid models. However, research gaps remain, particularly in unsupervised learning, real-world case studies, and the integration of IoT and cloud computing, underscoring the need for further research. The result also shows the need for innovative solutions to enhance the resilience and adaptability of district heating systems within the rapidly evolving energy landscape.

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KW - district heating

KW - artificial intelligence

KW - digitalization

KW - Scoping review

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DO - 10.1007/978-3-031-73500-4_11

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BT - Progress in Artificial Intelligence

A2 - Santos, Manuel Filipe

A2 - Machado, José

A2 - Novais, Paulo

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PB - Springer

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Y2 - 3 September 2024 through 6 September 2024

ER -

Ma ZG , Jørgensen BN. A Review of Intelligent Technologies in District Heating Systems. In Santos MF, Machado J, Novais P, Cortez P, Moreira PM, editors, Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part II. Springer. 2025. p. 123–134. (Lecture Notes in Computer Science, Vol. 14968). doi: 10.1007/978-3-031-73500-4_11

A Review of Intelligent Technologies in District Heating Systems

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Keywords

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