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Advances in District Heating and Cooling

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: 27 August 2026 | Viewed by 1838

Special Issue Editors


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Guest Editor
Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Energy Efficiency Department Research Center Bologna, Via dei Mille 21, 40121 Bologna, Italy
Interests: energy efficiency; numerical modelling; programming; data analysis

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Guest Editor
Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Energy Efficiency Department Research Center Bologna, Via dei Mille 21, 40121 Bologna, Italy
Interests: energy efficiency; numerical modelling; data analysis; renewable energy systems

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Guest Editor
Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Energy Efficiency Department, Research Center Casaccia, Via Anguillarese 301, S. Maria di Galeria, 00123 Rome, Italy
Interests: energy conversion systems for traditional and renewables sources; CHP/CCHP and district heating; energy efficiency in civil and industrial sectors; energy audits and monitoring; environmental impacts and containment technologies; energy efficiency and mini grid at high altitude; life cycle assessment (LCA) and carbon footprint of products and processes; carbon credits
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Special Issue Information

Dear Colleagues,

District heating and cooling (DHC) plays a key role in the energy transition by contributing to the decarbonization of thermal networks through the integration of renewable sources and waste heat. To meet new requirements for flexibility and sustainability, existing systems must improve efficiency; incorporate thermal energy storage; retrofit substations to operate as bidirectional systems; and adopt digital solutions to enable advanced monitoring, control, and optimization of network operations. Following the path of smart electricity grids, district heating and cooling are also expected to evolve into more dynamic and intelligent systems, capable of interacting with distributed generation and optimizing the use of available resources. 

In this context, this Special Issue aims to gather scientific contributions focused on district heating and cooling systems, with particular emphasis on modelling and optimization as essential tools for supporting informed decision-making while minimizing the need for physical interventions on infrastructure. Studies may include scenario-based analysis, real-world case studies, demonstration projects, and best practices. 

Topics of interest include, but are not limited to, the following: 

  • Design and retrofit optimization, from the component level (e.g., pipe sizing, layout, substation upgrades) to the entire system scale (e.g., pump schedules, temperature profiles).
  • Integration of renewable energy (e.g., solar thermal, geothermal, biomass) and waste heat. 
  • Bidirectional substations and smart network configurations.
  • Thermal prosumers in district networks.
  • Seasonal and short-term thermal energy storage solutions for network flexibility.
  • Digitalization and advanced control strategies.
  • IoT, SCADA, and sensor networks for real-time monitoring and control.
  • AI, machine learning, and data analytics for fault detection, predictive maintenance and control.
  • Smart grids, sector coupling, and flexibility services provided by DHC.
  • Mechanisms for sharing locally produced energy through energy communities.
  • Multi-objective optimization considering cost, emissions, and efficiency.
  • Decision-support tools for integrating DHC into urban development.
  • Regulatory and policy mechanisms supporting DHC decarbonization and digitalization.
  • Socio-economic analysis of DHC retrofits and expansions.
  • Lessons learned from decarbonization initiatives in different climatic and regulatory contexts.

Dr. Mattia Ricci
Dr. Federico Gianaroli
Dr. Paolo Sdringola
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • district heating
  • district cooling
  • prosumer
  • bidirectional substation
  • thermal grids
  • numerical modelling
  • experimental tests
  • waste heat
  • excess heat
  • self-consumption improvement
  • thermal energy community

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Published Papers (2 papers)

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Research

25 pages, 1033 KB  
Article
Public Acceptance and Socio-Economic Drivers of Renewable District Heating: Evidence from Italy
by Natalia Magnani, Enzo Loner, Chiara Ravetti, Francesca Mollo, Martina Capone and Elisa Guelpa
Energies 2026, 19(1), 96; https://doi.org/10.3390/en19010096 - 24 Dec 2025
Viewed by 800
Abstract
The decarbonisation of district heating (DH) is an important component of the European strategy to cut greenhouse-gas emissions, yet its feasibility depends as much on social and economic conditions as on technological innovation. The objective of this study is to assess how public [...] Read more.
The decarbonisation of district heating (DH) is an important component of the European strategy to cut greenhouse-gas emissions, yet its feasibility depends as much on social and economic conditions as on technological innovation. The objective of this study is to assess how public perceptions and socio-economic drivers shape acceptance of renewable energy sources (RES) in DH in Italy. Drawing on a survey of 1200 residents in Turin, we examine how public attitudes towards decarbonised heating options, the integration of renewables and demand-side flexibility are influenced by socio-economic characteristics. These characteristics include income, education, age, housing tenure, eco-awareness, trust in institutions, and technological affinity. Results show widespread support for the efficiency and comfort benefits of DH. However, the results also show a limited willingness to pay more for renewable heat, particularly among economically vulnerable groups. The study has important implications for policy strategies facilitating climate change mitigation and the transition towards adopting RES in DH. In particular, it contributes novel evidence on the social constraints that may limit the effective deployment of renewable DH and clarifies which levers—economic incentives, institutional trust, and clarity about benefits, as well as community engagement—can increase public acceptance. By identifying these conditions, the study shows how renewable DH can realistically support the EU’s decarbonisation agenda. Full article
(This article belongs to the Special Issue Advances in District Heating and Cooling)
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16 pages, 4550 KB  
Article
Multi-Step Artificial Neural Networks for Predicting Thermal Prosumer Energy Feed-In into District Heating Networks
by Mattia Ricci, Federico Gianaroli, Marcello Artioli, Simone Beozzo and Paolo Sdringola
Energies 2025, 18(24), 6608; https://doi.org/10.3390/en18246608 - 18 Dec 2025
Cited by 1 | Viewed by 607
Abstract
The heating and cooling sector accounts for nearly half of Europe’s energy consumption and remains heavily dependent on fossil fuels, emphasizing the urgent need for decarbonization. Simultaneously, the global shift toward renewable energy is accelerating, alongside growing interest in decentralized energy systems where [...] Read more.
The heating and cooling sector accounts for nearly half of Europe’s energy consumption and remains heavily dependent on fossil fuels, emphasizing the urgent need for decarbonization. Simultaneously, the global shift toward renewable energy is accelerating, alongside growing interest in decentralized energy systems where prosumers play a significant role. In this context, district heating and cooling networks, serving nearly 100 million people, are strategically important. In next-generation systems, thermal prosumers can feed-in locally produced or industrial waste heat into the network via bidirectional substations, allowing energy flows in both directions and enhancing system efficiency. The complexity of these networks, with numerous users and interacting heat flows, requires advanced predictive models to manage large volumes of data and multiple variables. This work presents the development of a predictive model based on artificial neural networks (ANNs) for forecasting excess thermal renewable energy from a bidirectional substation. The numerical model of a substation prototype designed by ENEA provided the physical data for the ANN training. Thirteen years of simulation results, combined with extensive meteorological data from ECMWF, were used to train and to test a multi-step ANN capable of forecasting the six-hour thermal power feed-in horizon using data from the preceding 24 h, improving operational planning and control strategies. The ANN model demonstrates high predictive capability and robustness in replicating thermal power dynamics. Accuracy remains high for horizons up to six hours, with MAE ranging from 279 W to 1196 W, RMSE from 662 W to 3096 W, and R2 from 0.992 to 0.823. Overall, the ANN satisfactorily reproduces the behavior of the bidirectional substation even over extended forecasting horizons. Full article
(This article belongs to the Special Issue Advances in District Heating and Cooling)
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