District Heating System Research Articles

Quantifying the decarbonization potential of mobile heat battery in low-temperature district heating

This research assesses the potential of a mobile thermochemical storage system, the mobile heat battery (M-HB), for decarbonizing a low-temperature district heating (DH) system in the Netherlands. The assessment is built on a case study where the M-HB is used to transport waste heat from different sources to a neighborhood interface of a DH system. This case study utilizes a simulation-based methodology to calculate the emissions from grid electricity, DH, and M-HB transport and charging. Building performance simulation is used as the main experimental method in combination with both empirical data and theoretical assumptions. Various system operational strategies and uncertain factors are explored, and waste heat sources are screened by different decarbonization targets. Findings indicate that using the M-HB can reduce the operational carbon emissions by up to 80 %, from approximately 60–70 KgCO2/GJ of the system without M-HB to around 13 KgCO2/GJ in optimal scenarios. Emissions from M-HB transport and charging are identified as more influential to the decarbonization potential than other considered factors, which addresses the significance of choosing proper waste heat sources. Despite some limitations from data availability and assumptions, this work identifies both opportunities and challenges for using M-HB to decarbonize DH systems.

Booster heat pump with drop-in zeotropic mixtures applied in ultra-low temperature district heating system

The pursuit of sustainable district heating solutions has driven a growing interest in ultra-low temperature district heating (ULTDH) systems, where booster heat pumps (BHPs) play a pivotal role despite challenges posed by their efficiency limitations under large temperature glide conditions. This paper investigates the potential of drop-in R-1234yf/R-32 zeotropic mixtures in BHPs compared to a baseline R-134a system, within the context of a ULTDH framework. This study focused on the viability of the mixtures of R-1234yf/R-32 with the composition ratio of 80 %/20 % and 90 %/10 %. The investigation reveals disparities in compressor efficiency and heat exchanger pressure drop at the component level. Device-level analysis unveils increased COP for R-1234yf/R-32 mixtures, alongside with maximum second-law efficiencies reaching 0.32. A remarkable enhancement in heating capacity up to 58 % was found. System-level analysis demonstrated exergetic efficiencies and identified preferable district heating temperatures. Exergetic efficiencies of 0.47, 0.55, and 0.59 were achieved for domestic hot water preparation at district heating supply temperatures of 30 °C, 35 °C, and 40 °C, with a subsequent shift in optimal district heating temperatures as central heating station efficiency decreased. Temperature profile analysis underscored challenges stemming from excessive subcooling, highlighting the need for configuration refinements.

Process design, performance comparison and operating test of the multi-stage vertical absorption heat exchanger realizing independent heating in three zones

Absorption heat exchangers applied in district heating systems can significantly reduce the outlet water temperature of the primary network, thereby expanding the heating scale and promoting low-temperature waste heat recovery. However, nearly 50% of the existing heating systems in high-rise buildings are divided into three independent zones. At present, there is a lack of research for absorption heat exchangers in this scenario. The main task of this paper is to address this issue to expand the application range of absorption heat exchangers. Firstly, two different processes are designed in this paper. The first process is to add a plate heat exchanger in the existing two-stage process, while the second process is a novel three-stage vertical process, consisting of three absorption heat pumps with different pressures and three sets of plate heat exchangers. Then, the operating performance, self-adjustment ability and the system cost of different processes are compared based on the simulation method. Although the price of Process 2 is 26.4% higher than that of Process 1, the efficiency of Process 2 is 20.3%-27.7% higher, and the self-regulation ability is significantly better. Thus, Process 2 has better overall performance. Moreover, the system development and operating test of Process 2 are conducted. Throughout the whole heating season, the overall efficiency of the system is 1.17–1.23. Without manual intervention, the relative standard deviations of the inlet water temperature of the secondary network and the actual heat supply rate ratio are less than 5% and 16% respectively, which proves that the system has great self-adjustment ability. The conclusions in this paper can guide the design and application of the absorption heat exchanger in three-zone independent heating scenarios.

Role of power-to-heat and thermal energy storage in decarbonization of district heating

The sector integration of the heat and electricity sectors promotes the flexibility of the energy system. This, together with the already almost carbon dioxide-free electricity supply in Finland, facilitates the environmental transition to a carbon-neutral heating system. In this study, pathways to decarbonize the district heating system in Åland (an autonomous region of Finland) are explored. Especially, the roles of different power-to-heat technologies, e.g., heat pumps and direct electric heating, and thermal energy storage are investigated in the decarbonization of the district heating system. The focus is on studying the impact of varying prices in electricity markets on the operation of climate-neutral district heating systems. For this, three scenarios were modeled over the five years of 2018–2022 with varying demand and electricity market prices by using the modeling software PLEXOS. The study showed that electricity prices, but also reserve market prices, have a very significant impact on the operation cost and profit of a district heating system. Overall, electrification has the strong potential to reduce emissions cost-effectively in a district heating system, but it also makes the system vulnerable to electricity price volatility. It can be concluded that thermal energy storage and reserve market participation are crucial for protecting against cost increases and reducing investment risk.

Dynamic performance analysis of a new low-temperature nuclear heating system with APROS

ABSTRACT Pool-type low-temperature heating reactor (PLTHR) has attracted considerable attention throughout the world due to its low operating parameters and satisfactory inherent safety in district heating. Exploring the dynamic performance of PLTHR is a prerequisite for designing control systems and developing operation strategies. Until now, the dynamic performance of the district heating system using a 400 MW pool-type low-temperature heating reactor (DHR-400) has not been fully discussed. Based on APROS software, a precise dynamic model for DHR-400 is constructed in this paper. The dynamic responses of DHR-400 under five external variables such as control rod reactivity, first loop flow rate, second loop flow rate, third loop flow rate, and return temperature at the third loop are investigated. The results revealed that the core power variation is not linear with the flow rate variation at the three loops. Core power variations are −16.27, −14.04, and −20.96 MW with a 30% reduction in flow rate at the first loop, the second loop, and the third loop, respectively. Considering safe operation, when there are minor fluctuations in the heating demand, the core power regulation method by adjusting the third loop’s flow rate should be given priority without altering the position of the control rods.

Piping network optimization for district heating system using an enhanced Genetic Algorithm searching method

Given the substantial construction and operational expenses associated with a district heating system (DHS), achieving an optimal layout for the piping network is paramount for its successful deployment. In this study, the optimization of DHS piping configuration has been explored. Traditional exhaustive search methods for network design are often impractical due to computational constraints, making Genetic Algorithm (GA) a preferred alternative for navigating the vast search space of optimization problems efficiently. However, GA, which relies on probabilistic heuristics, may not always pinpoints the most effective solutions, particularly those in close proximity to the current near-optimal configuration. To address this issue, an enhanced GA-based neighboring search method for identifying optimal or near-optimal piping layout for DHS more effectively has been developed in this study. When a local minimum is detected in the GA optimization process, the method initiates a neighboring search by selecting an elite candidate. The link with the highest piping cost from the elite candidate's configuration is identified. Subsequently, one of the other nodes in the configuration is connected to the nodes of the identified link to explore solutions beyond the local optimum. This new approach was firstly validated against an Optimal Communication Spanning Tree (OCST) benchmark problem, where it demonstrated superior efficacy by achieving higher success rate and quicker first-hit generation compared to conventional GA method. Specifically, this method showed a 60 % success rate with a minimum first-hit generation number of 140, outperforming the traditional GA's 40 % success rate and 263 generations. Further modification to the OCST benchmark to better simulate a real-world DHS application underscored the ability of this neighboring search method to exceed the previously established optimal configuration, uncovering a “better' solution with superior fitness value. This promising methodology was subsequently applied to the hypothetical design of a DHS piping network, illustrating its potential to enhance the planning and implementation of efficient, cost-effective district heating systems.

Фінансові перешкоди впровадженню теплових насосів в централізованому теплопостачанні

The use of powerful industrial heat pumps (HP) is a fairly effective means of rational and environmentally friendly use of energy resources both in individual households and in district heating (DH), as well as in production processes in various industries. Powerful HPs are used in Ukraine much less than in developed European countries. In fact, these are isolated cases. The post-war reconstruction of destroyed cities with their district heating systems gives Ukraine a unique chance to use modern energy-efficient technologies, including HP. As a result, efficiency will improve and DH competitiveness will increase due to the low cost of thermal energy for consumers. Almost all developed countries of the world have government financial support for the HP implementation. The purpose of this study is to determine the level and form of government financial support for projects to implement HP in DHs of Ukraine. Financial modeling of the implementation of heat pump plants shown that they are more expediently to be used in the mode of generating thermal energy than in the mode of regulating the electric load of power systems. It is shown that the projects of heat pump plants, which use the heat of flue gases as a source of low-potential heat (LPH), are the most economically attractive and practically do not require government financial support. Projects of heat pump plants, which use air, ventilation emissions, waste water, soil and groundwater, sea, rivers, and waste heat of technological processes as LPH, are not financially attractive without government financial support, and some of them are even unprofitable. The most appropriate comprehensive financial support is tax incentives and interest compensation on the loan. Sensitivity analysis showed that projects for the implementation of heat pump plants may be the most sensitive to the amount of generated thermal energy, the price of natural gas and electricity. Keywords: heat pumps, low-potential heat sources, district heating, financial obstacles, tax incentives, grants.

Heat–power decoupling for the CHP unit by utilizing heat storage in the district heating system integrated with heat pumps: Dynamic modeling and performance analysis

Heat–power decoupling is a key issue to be addressed for the combined heat and power (CHP) unit to enhance its operational flexibility, and utilizing heat storage in district heating systems represents a viable approach. The widespread adoption of heat pumps to boost heating network also increases the complexity of managing heat storage, and the quantitative impact of heat storage has significant implications during operation. To this end, dynamic models of heating networks and heat pumps were developed. A metric, the maximum maintenance time, was established to quantitatively assess heat storage utilization. Dynamic simulations and performance analyses were conducted on a 330 MW CHP unit. The results indicate that by employing heat storage, the feasible maximum and minimum output power of the heating system can be increased by 20 MW and decreased by 45.5 MW, respectively. With the integration of a heat pump, these values can further increase by 9 MW and decrease by 158 MW, respectively, significantly enhancing the operational flexibility of CHP unit.

Diversifying heat sources in China’s urban district heating systems will reduce risk of carbon lock-in

Diversifying heat sources in China’s urban district heating systems will reduce risk of carbon lock-in

Use of a low-cost phase change material emulsion in de-centralized thermal energy storage for district heating network enlargement

A detailed heat transfer model of a storage tank was developed to assess the performance of a district heating system with de-centralized storage solutions. The performance of two cases, with water and a low-cost phase change material emulsion as storage medium was analysed for 40 residential buildings in Zaragoza (Spain). The chosen configuration is a typical cylindrical tank with internal coils through which the district heating water flows for the charge and discharge. This decentralized thermal energy storage unit reduced peak demand and mass flow in the network, allowing additional buildings to connect to a saturated grid. Four configurations were examined: (1) A 180 m3 water tank reduced district heating power demand by 36.6 %. (2) The same 180 m3 tank using the emulsion required fewer coils, lowering costs, stabilizing TES temperature, and increasing water supply temperature, thus extending system lifespan. (3) A 130 m³ tank with the emulsion offered operational characteristics similar to the water tank, with economic and structural benefits from reduced size. (4) An 180 m³ optimised tank with the emulsion achieved a 38.8 % reduction in district heating power demand. These configurations demonstrate the efficiency and cost-effectiveness of using phase change material emulsion in thermal energy storage systems.

Physics-Informed Neural Network Modeling and Predictive Control of District Heating Systems

Physics-Informed Neural Network Modeling and Predictive Control of District Heating Systems

Strategies for decarbonizing European district heating: Evaluation of their effectiveness in Sweden, France, Germany, and Poland

Decarbonizing the EU's district heating is crucial for meeting climate goals and securing a sustainable energy future. Currently, district heating suffers from inefficiency, high operating temperatures, significant distribution losses, and reliance on fossil fuels. Literature highlights strategies for reducing emissions, including integrating low-carbon heat sources, lowering supply temperatures, and employing efficient technologies like heat pumps and combined heat and power (CHP). However, the individual effectiveness of these strategies in reducing emissions within existing networks remains unassessed. This study addresses the gap by applying a comprehensive model that evaluates energy and emissions across the district heating supply chain, coupled with a derivative-based sensitivity analysis. We apply this methodology to the national-level district heating systems of Sweden, France, Germany, and Poland. Results indicate that the impact of decarbonization strategies on district heating emissions varies significantly by the system's characteristics, i.e., the energy mix in power and district heating supply and the presence of CHP plants. Primarily, incorporating more low-carbon heat sources emerges as the most effective method for emission reduction across nearly all examined countries. A 1 % increase in the share of low-carbon heat sources can potentially cut emissions by 0.8–1.3 kg CO2e per GJ of heat. In countries like Sweden and France, where the power generation already relies heavily on low-carbon resources, technologies which convert electricity to heat—such as heat pumps and electric boilers—rank as the second most effective approach. In contrast, for countries like Germany and Poland, with their moderate to low use of low-carbon power, reducing distribution losses and decreasing heat demand prove more effective, with emission reductions ranging between 0.8-1.3 and 0.7–1.2 kg CO2e per GJ in these countries, respectively. Additionally, cutting down power generation in fossil fuel-based CHP plants significantly reduces emissions in these regions. While green hydrogen and carbon capture and storage (CCS) also contribute to emission reductions, a 1 % increase in green hydrogen's share might decrease emissions by just 0.3–0.5 kg CO2e per GJ of heat, highlighting their lower effectiveness compared to the aforementioned strategies. These insights hold value for both district heating operators and for technology suppliers seeking decarbonization pathways. This is also true for policymakers focused on climate change mitigation, guiding the distribution of subsidies and R&D investments.

A method for setting room temperature of district heating in northern China based on local thermal comfort

Currently, the district heating system in northern China primarily employs two types of terminals, namely radiators and radiant floors. The heating design temperature is set for the center of the room without considering local thermal comfort for individuals. As the real thermal environment within buildings is non-uniform, variations in thermal sensation across different parts of the body will affect whole-body thermal comfort. Therefore, it is crucial to prioritize local thermal comfort when setting room temperatures for heating purposes. In this study, we analyzed the data from the chamber experiments and Chinese Thermal Comfort Database, focusing on the district heating environments of residences, office buildings, and university classrooms in severe cold and cold zones. We developed a thermal sensation evaluation model for analyzing the most uncomfortable body part, investigated the lower limit of acceptable air temperature for this specific body part and inferred appropriate setpoint based on both this limit and head-ankle temperature difference. The results indicate that ankles are the most uncomfortable part with an estimated lower limit of acceptable air temperature at approximately 18 °C. Consequently, we recommend setting room temperatures of 20 °C for radiator heating (RH) and 19 °C for floor heating (FH) to ensure ankle thermal comfort. The findings of this study can provide theoretical basis for reasonable settings of heating room temperature for the aforementioned three types of buildings in northern China, thereby further achieving energy conservation.

A refined classification method of heat customers to improve inter-household thermal balance intelligent control and regulation

Hydraulic imbalance in district heating systems (DHSs) especially in the secondary pipe network hinders the improvement of system energy efficiency. To improve inter-household thermal balance on the secondary side, this paper proposes a refined classification and intelligent regulation method for heat customers. Firstly, an intelligent balancing system is proposed with the smart valves installed at heat customer's thermal entrance. Then, the refined method classifies the heat customers based on room comprehensive thermal characteristic coefficient. The regulation periods and target return temperature predictive models are determined for each customer type to achieve balance regulation. Finally, the proposed intelligent balance system was applied to a practical DHS secondary pipe network to verify its balance effect. After the regulation, indoor temperature non-uniformity coefficient for each type of heat customer decreased by 15 %; while the return water temperature dispersion reduced by 8 %–18 %. This led to a significant improvement in hydraulic and thermal balance among heat customers, resulting in a 6.2 % heat-saving rate. The application provides a reference for inter-household thermal balance regulation in scenarios where indoor temperature loggers are limited within similar secondary pipe network of DHSs.

Design and simulation of district heating networks: A review of modeling approaches and tools

District heating (DH) systems have been identified as an important component in efforts to mitigate greenhouse gas emissions and achieve climate targets in the near future. Software tools for analyzing these systems use different modeling approaches, making it challenging for practitioners to choose the most suitable tool based on specific use case requirements. This paper systematically reviews available DH network modeling and simulation tools, comparing their modeling approaches, application scope, and functional capabilities. An online survey was conducted among DH tool developers and experts to assess the technical evaluation criteria for these tools. First, the basic concepts and principles of DH networks modeling are discussed. Moreover, it provides an overview of DH network mathematical models, and discusses various numerical methods used for simulation and analysis, while highlighting potential areas for further research and tools development. The aim of this paper is to support academic and industrial users in selecting appropriate modeling approaches, tools, and libraries.

Sparse dynamic graph learning for district heat load forecasting

Accurate heat load forecasting is crucial for the efficient operation and management of district heating systems. This study introduces a novel Sparse Dynamic Graph Neural Network (SDGNN) framework designed to address the complexities of forecasting heat load in district heating networks. The proposed model represents the district heating network as a dynamic graph, with nodes corresponding to consumers or heat sources and edges denoting temporal dependencies. The SDGNN framework comprises three key components: (1) a sparse graph learning module that identifies the most relevant nodes and edges, (2) a spatio-temporal memory enhancement module that captures both short-term and long-term dependencies, and (3) a temporal fusion module that integrates node representations into a comprehensive global forecast. Evaluated on a real-world district heating dataset from Denmark, the SDGNN model demonstrates superior accuracy and efficiency compared to existing methods. The results indicate that the SDGNN framework effectively captures intricate spatio-temporal patterns in historical heat load data, achieving up to 5.7% improvement in RMSE, 7.4% in MAE, and 5.7% in CVRMSE over baseline models. Additionally, incorporating meteorological factors into the model further enhances its predictive performance. These findings suggest that the SDGNN framework is a robust and scalable solution for district heat load forecasting, with potential applications in other domains involving spatio-temporal graph data.

The state of district heating and cooling in Europe - A literature-based assessment

District heating and cooling systems have been present on the European market for more than a century, constantly evolving into more efficient energy infrastructures important for decarbonization of the heating and cooling sectors. With roughly 17,000 operational district heating systems, serving over 70 million citizens, currently, the final energy consumption attributed to district heating in Europe is estimated at over 450 TWh. As the European district heating and cooling sector varies extensively in every analyzed aspect, there are vast differences between European countries regarding technical preferences, technological development, market structure and regulatory frameworks of these systems. The main purpose of this paper is to provide a comprehensive overview of the present status of the district heating and cooling systems in Europe with insight(s) and suggestions into future trends. In addition, the provided data serves as a valuable baseline for future research. Finally, this paper draws attention to the new socio-demographic approach, observed when analyzing the district heating and cooling systems, that has been recently introduced into the scientific community. This new approach also reveals the opportunity for creating new indicators that will influence the modeling of existing and future district heating and cooling systems.

Solar district heating system with large heat storage: Energy, exergy, economic and environmental (4E) analysis

In the context of the global energy crisis and climate change, solar district heating systems are an essential technology that can mitigate this problem. To accelerate the transition to sustainability, a proven solar district heating system and an analysis method are needed to serve as a role model. For this purpose, a techno-economic analysis method is proposed in this study. It consists of a bi-directional long short-term memory method for correcting outlier data and a balanced method for energy and exergy analyses. The solar district heating system with large-scale thermal storage in Dronninglund, Denmark, is investigated in detail. The design of this system is centered on an integrated control strategy that synchronizes the solar collector loop, the energy storage loop, and the heating load loop to improve overall efficiency. The results show an increase in solar collector efficiency to 41 %, thermal storage efficiency to 89 %, and a coefficient of performance to 1.74 for the absorption heat pump. This integration increases the system’s coefficient of performance dramatically to 2.9, with a renewable energy percentage of 77 %. Exergy analysis shows a storage exergy of 68 % and a heat pump exergy of 49 %, which suggests that the system has a highly efficient energy conversion. The annual heating demand for the industrial and residential branches is 7,450 MWh and 28,100 MWh, respectively, which are covered by solar (42 %), biomass oil (35 %), and natural gas (23 %). The economic assessment shows that the net present value could rise from −5.5 million euros over 10 years to 15.2 million euros over 40 years, indicating long-term economic advantages. The system achieves 122 kg/MWh of carbon reduction with a 0.92 carbon neutrality factor, which is carbon neutral. This study provides a compelling case for deploying large-scale solar heating systems, offering a robust analysis method and insightful findings for technological developments and economic optimizations.

Two-stage optimization model for day-ahead scheduling of electricity- heat microgrids with solid electric thermal storage considering heat flexibility

Traditional electricity-heat microgrid (EHM) is limited in flexibility due to real-time balancing between the supply and demand of electric and heat system. The heat flexibility (HF) can be released by thermal inertia and heat storage characteristics of district heating systems (DHS) and heat storage units, and it can be used to increase the electric power flexibility (EF) of EHM. In this paper, the quantitative relationship between HF and EF is investigated, and a two-stage optimization model for day-ahead scheduling of EHM with solid electric thermal storage (SETS) is established. Firstly, the electric-heat flexibility conversion coefficient (EHFC) is developed to decide the allocation of HF among different electricity-heat coupling units, such as CHP and SETS, and EF supply model of EHM based on HF is built. Secondly, a two-stage optimization model is proposed for day-ahead scheduling of EHM to improve EF and economy of EHM by optimizing the heating power and HF's allocation. Thirdly, the equivalent energy storage of the DHS is quantitatively analyzed, providing a reference for planning and operating of EHM's flexibility resource. Finally, the case study shows that by considering HF and deploying SETS, the total cost can be reduced by 18.8 % and 22.6 %, respectively.

Semi-decentralized temperature control in district heating systems

The supply temperature in district heating systems has traditionally been controlled using feedforward – a robust and well-validated approach for district heating networks with few producers and relatively high supply temperatures. The transition towards lower temperature district heating networks allows for efficient reuse of excess heat from, e.g., industrial processes and data centers. Excess heat is often intermittent, cannot always be assumed to be possible to control with a centralized controller, and can cause temperature disturbances in the grid. Closing the loop using PID control is challenging due to the process’s time-varying nature and long time delays. Model Predictive Control (MPC) suffers from a higher complexity, long computational times, and the need for a well-validated and maintained centralized model. The paper suggests a semi-decentralized approach using the Smith predictor with an event-driven assignment of active controllers and sensors. A reduced order model based on a more comprehensive state space model is derived and used for gain scheduling and input–output pairing using the normalized relative gain array. The focus is on temperature disturbance rejection, and appropriate tuning rules and controller structures are suggested. Simulation results show that the proposed control structure can handle various types of temperature disturbances, even in the presence of model estimation errors.