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Digital Transformation of District Heating : A Scoping Review of Technological Innovation, Business Model Evolution, and Policy Integration

Ma, Zheng Grace and Lygnerud, Kristina LU (2025) In Energies 18(22).
Abstract

District heating is critical for low-carbon urban energy systems, yet most networks remain centralized in both heat generation and data ownership, fossil-dependent, and poorly integrated with digital, customer-centric, and market-responsive solutions. While artificial intelligence (AI), the Internet of Things (IoT), and automation offer transformative opportunities, their adoption raises complex challenges related to business models, regulation, and consumer trust. This paper addresses the absence of a comprehensive synthesis linking technological innovation, business-model evolution, and institutional adaptation in the digital transformation of district heating. Using the PRISMA-ScR methodology, this review systematically analyzed 69... (More)

District heating is critical for low-carbon urban energy systems, yet most networks remain centralized in both heat generation and data ownership, fossil-dependent, and poorly integrated with digital, customer-centric, and market-responsive solutions. While artificial intelligence (AI), the Internet of Things (IoT), and automation offer transformative opportunities, their adoption raises complex challenges related to business models, regulation, and consumer trust. This paper addresses the absence of a comprehensive synthesis linking technological innovation, business-model evolution, and institutional adaptation in the digital transformation of district heating. Using the PRISMA-ScR methodology, this review systematically analyzed 69 peer-reviewed studies published between 2006 and 2024 across four thematic domains: digital technologies and automation, business-model innovation, customer engagement and value creation, and challenges and implementation barriers. The results reveal that research overwhelmingly emphasizes technical optimization, such as AI-driven forecasting and IoT-based fault detection, whereas economic scalability, regulatory readiness, and user participation remain underexplored. Studies on business-model innovation highlight emerging approaches such as dynamic pricing, co-ownership, and sector coupling, yet few evaluate financial or policy feasibility. Evidence on customer engagement shows increasing attention to real-time data platforms and prosumer participation, but also persistent barriers related to privacy, digital literacy, and equity. The review develops a schematic conceptual framework illustrating the interactions among technology, business, and governance layers, demonstrating that successful digitalization depends on alignment between innovation capacity, market design, and institutional flexibility.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
artificial intelligence, business model innovation, digital transformation, district heating, scoping review
in
Energies
volume
18
issue
22
article number
5994
publisher
MDPI AG
external identifiers
  • scopus:105023135649
ISSN
1996-1073
DOI
10.3390/en18225994
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 by the authors.
id
f69cb18c-ea09-4cae-aa24-0ffc4f74bbe9
date added to LUP
2026-01-22 13:36:44
date last changed
2026-01-22 13:37:14
@article{f69cb18c-ea09-4cae-aa24-0ffc4f74bbe9,
  abstract     = {{<p>District heating is critical for low-carbon urban energy systems, yet most networks remain centralized in both heat generation and data ownership, fossil-dependent, and poorly integrated with digital, customer-centric, and market-responsive solutions. While artificial intelligence (AI), the Internet of Things (IoT), and automation offer transformative opportunities, their adoption raises complex challenges related to business models, regulation, and consumer trust. This paper addresses the absence of a comprehensive synthesis linking technological innovation, business-model evolution, and institutional adaptation in the digital transformation of district heating. Using the PRISMA-ScR methodology, this review systematically analyzed 69 peer-reviewed studies published between 2006 and 2024 across four thematic domains: digital technologies and automation, business-model innovation, customer engagement and value creation, and challenges and implementation barriers. The results reveal that research overwhelmingly emphasizes technical optimization, such as AI-driven forecasting and IoT-based fault detection, whereas economic scalability, regulatory readiness, and user participation remain underexplored. Studies on business-model innovation highlight emerging approaches such as dynamic pricing, co-ownership, and sector coupling, yet few evaluate financial or policy feasibility. Evidence on customer engagement shows increasing attention to real-time data platforms and prosumer participation, but also persistent barriers related to privacy, digital literacy, and equity. The review develops a schematic conceptual framework illustrating the interactions among technology, business, and governance layers, demonstrating that successful digitalization depends on alignment between innovation capacity, market design, and institutional flexibility.</p>}},
  author       = {{Ma, Zheng Grace and Lygnerud, Kristina}},
  issn         = {{1996-1073}},
  keywords     = {{artificial intelligence; business model innovation; digital transformation; district heating; scoping review}},
  language     = {{eng}},
  number       = {{22}},
  publisher    = {{MDPI AG}},
  series       = {{Energies}},
  title        = {{Digital Transformation of District Heating : A Scoping Review of Technological Innovation, Business Model Evolution, and Policy Integration}},
  url          = {{http://dx.doi.org/10.3390/en18225994}},
  doi          = {{10.3390/en18225994}},
  volume       = {{18}},
  year         = {{2025}},
}