Buildings are increasingly becoming smarter due to the widespread availability of connected devices, sen-sors, and actuators. These technologies enhance indoor comfort while reducing operational costs, energy consumption, and environmental footprints. However, space and domestic hot water heating continue to significantly contribute to CO2 emissions in the building sector. This emphasizes the urgent need to decar-bonize energy systems and transition from fossil fuels toward renewable energy sources to mitigate climate change, improve energy supply security, reduce pollution, and address sustainability challenges necessi-tates a significant paradigm shift in the building sector, which is the largest energy end-user. Buildings are evolving into more responsive loads with decentralized energy production and storage capabilities. This transformation allows buildings to operate in synergy with various energy sectors, adapting their short-term energy demand profiles, thereby helping to align energy demand with the intermittent supply from renewa-ble energy sources.
District heating and cooling (DHC) systems are recognized as sustainable solutions for meeting heating and cooling needs in densely populated areas, playing a pivotal role in global decarbonization efforts by promoting the use of renewable energy and enhancing the flexibility of energy supply. Within the context of DHC the concept or energy-flexible buildings, which utilizes buildings as decentralized solutions for thermal storage, is also gaining traction. Despite the potential of DSM and the utilization of buildings for energy storage within DHC systems, several challenges hinder large-scale implementation, necessitating close collaboration among various stakeholders with sometimes conflicting goals. These factors underscore the need for innovative approaches in DSM to facilitate an effective energy transition and achieve climate tar-gets.
The IEA EBC Annex 84, titled “Demand Management of Buildings in Thermal Networks,” aims to develop comprehensive guidelines for the successful activation of Demand Response (DR) in District Heating and Cooling (DHC) systems. It addresses both social and technical challenges while leveraging digitalization, such as smart meters and sensors, to enhance large-scale DR implementation with minimal investment. Specific objectives include providing knowledge on key stakeholders, proposing design solutions for build-ing heating and cooling installations, and developing methods to utilize data from monitoring equipment for real-time modelling of thermal demand response.
Within Annex 84, Subtask D focuses on reviewing existing buildings that can deliver thermal storage to DHC systems, examining the technological solutions and collaboration strategies in place. Through these efforts, Annex 84 aims to promote best practices and facilitate the effective integration of demand response in thermal networks. To achieve this, the case study questionnaire developed for Subtask D serves as a standardized framework for collecting and documenting relevant information about DSM implementations and projects in district heating (DH) networks.
The questionnaire systematically gathers comprehensive and comparable data from diverse case studies, enabling the analysis and assessment of DSM methods and their effectiveness across various projects. By providing researchers and practitioners with a structured format to submit key parameters, the question-naire facilitates comparative analysis and knowledge transfer between different implementations. It consists of several thematic chapters that include both open and multiple-choice questions, collecting information about the buildings investigated, the energy storage technologies used, the thermal grid characteristics, and the specific type of DSM applied, along with its intended purpose and expected benefits.
In total 29 case studies on DSM in DH networks have been collected and analysed. Each case study is as-sociated with a distinct research project involving various stakeholders, including universities, research institutions, and private companies, often collaborating in consortiums. The projects span from 2010 to 2025, predominantly located in European countries, particularly Denmark and Germany, reflecting a strong interest in implementing DSM within buildings connected to DH networks. A concise summary of each pro-ject, highlighting key information, is presented in
Table 2, together with a classification of the status of the research project and the DSM implementation progress.
To facilitate the dissemination of the case study analysis a case study brochure1 and a presentation with case study profiles2 have been created. The primary intent of the case study brochure is to showcase prac-tical implementations and facilitate stakeholder understanding of successful projects through visually en-gaging and accessible content on a higher level. The case study profiles on DSM in DH networks serve to provide a standardized and categorized summary of all 29 case studies, promoting consistent analysis and comparison across various projects. Each profile is visually structured for enhanced readability, covering essential categories such as project overview, objectives, system boundaries, and results. This systematic documentation facilitates effective analysis and application of STD findings, making the profiles a valuable resource for understanding DSM in practice.
The comparative analysis of the collected case studies within this report provides insights into various ap-proaches and best practices. Among the 29 case studies, 23 are from completed projects, with an average project duration of three years. The case studies encompass a variety of scales, including individual build-ings and larger networks, with seven focused on single buildings and the remainder involving multiple structures, often utilizing only a portion of the connected heating networks for experimental purposes. The analysis reveals that most projects pursue technical objectives, emphasizing the testing of new innovations to mitigate peak loads commonly occurring in the morning. Seven projects utilize predictive control strate-gies to optimize energy demand forecasts and manage loads effectively. Additionally, seven case studies examine the thermal mass of buildings as a resource for load shifting, while ten projects specifically engage consumers to investigate acceptance and user behaviour related to demand response measures. Addition-ally, the comparative analysis highlights the technology readiness levels (TRL) of the projects, with the ma-jority at TRL seven, also indicating a focus on existing buildings and networks rather than new construc-tions. Residential buildings dominate the research, with a notable emphasis on apartments and single-fam-ily homes. Furthermore, the types of DH networks utilized vary, with a significant number focusing on sec-ond and third generation networks that cater to both space heating and domestic hot water needs.
The comparative analysis of the collected case studies regarding Demand-Side Management (DSM) re-veals that thermal energy storage is the predominant storage type utilized, with a total of 27 systems identi-fied. Among these, 21 are decentralized, with 17 leveraging building mass as part of their storage strategy. Only one project is dedicated to supplying space cooling, which is located outside the district heating net-work context.
Furthermore, the analysis indicates that 22 case studies, focus, among other aspects, on load shifting as a primary purpose of the investigated DSM measures. Other objectives include load shedding and efficiency improvements, with 12 of case studies incorporating load shedding as a goal. The anticipated benefits of the DSM measures mainly extend to the DH grid operator and indirectly to customers, with 13 case studies benefiting this way. Additionally, six case studies provide direct benefits to both the DH grid operator and customers. There are five case studies where only the DH grid operator benefits, and just one case study exclusively benefits customers. Cost reduction is a common objective, as seen in 14 case studies aimed at decreasing expenses associated with peak boiler operation. In case 14, 14.36% of energy could be saved leading to cost reductions. 7 case studies aim to lower CO2 emissions. For example, case 23 is expecting to save 25.000 tons of CO2 by reducing peak boiler operation run by gas. Approximately half of the case studies investigate DSM measures activated by the DH operator. Various approaches to DSM implementa-tion are observed, including active and indirect measures, collective measures (such as installing smart home technology), and tariff structures. Most studies focus on the interaction between buildings and the grid, with daily load management being the standard timescale for implementation.
The lessons learned from the case studies are categorized into two groups: 1) User behaviour, thermal comfort, and acceptance, and 2) Flexibility sources, DSM strategies and technical aspects.
Successful implementation of DSM requires a nuanced understanding of buildings and occupants as unique entities rather than simple load points. Temperature conditions can vary significantly within a build-ing, necessitating decentralized control strategies that manage room-level variations while ensuring occu-pant comfort. Effective communication about the functions and benefits of demand response (DR) interven-tions enhances acceptance, with key factors influencing acceptance including appropriate indoor climate conditions, timing of load shifts, and individual control options for occupants. Occupants are more likely to accept DSM measures when they are well-informed about the benefits, including economic savings and contributions to collective societal goals. Financial incentives also play a crucial role in motivating participa-tion in DSM programs, particularly when combined with environmental benefits. The analysis emphasizes the importance of maintaining temperatures within comfort boundaries, as residents generally accept fluctu-ations as long as they remain comfortable.
Additionally, successful DSM implementation hinges on collaboration among multiple stakeholders, with thorough communication and consultation processes deemed essential. The technical aspects highlight that utilizing building thermal mass effectively increases flexibility in district heating systems, while specific strategies for peak load management can significantly reduce demand during critical periods. Advanced control systems and economic model predictive control can enhance the effectiveness of load shifting strat-egies but must be tailored to individual room requirements to prevent issues like overheating. Overall, a ho-listic approach that incorporates user preferences and technical innovations is crucial for the success of DSM initiatives in thermal networks.
Based on the lessons learned from the case studies, several key recommendations for stakeholders in-volved in DSM implementation in buildings connected to DH grids are proposed. By following these recom-mendations, stakeholders can enhance the effectiveness of DSM initiatives, improving energy efficiency in district heating systems.
Building and System Considerations: Implement decentralized room-level control strategies and recog-nize heavy buildings as valuable thermal storage assets. Quantify thermal storage capacity in degree hours and prioritize targeted preheating in specific zones. Short intervention periods can achieve peak reductions, and hybrid networks should be explored for summer shutdowns to reduce energy losses.
Control Strategies and Technology: Coordinate DSM triggers with energy management systems and ex-tend prediction horizons in demand forecasts. Avoid partial control of radiators in E-MPC implementations and prioritize domestic hot water during peak periods. Ensure thermostats remain on to prevent condensa-tion and maintain minimum temperatures.
Occupant Engagement and Communication: Clearly explain DSM functions and benefits to occupants before implementation. Frame participation as a collective achievement and emphasize economic and en-vironmental benefits. Allow occupants some control over temperature settings and provide app notifications with personalized recommendations.
DSM Implementation Approach: Address building-related issues before implementing DSM and design shorter demand response events for high override risk buildings. Simple, cost-effective data-driven DSM solutions should be prioritized, and thorough stakeholder consultation is essential.
Pitfalls to Avoid: Avoid treating buildings as simple load points, creating new demand peaks, and ignoring occupant engagement. Do not reduce temperatures during already cold periods, and refrain from overly complex solutions when simpler alternatives exist.