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The combined production of electricity and thermal energy (combined heat and power or co-generation) is the most efficient and convenient approach to reduce costs for energy at industrial power plants and district heating plants that use natural gas as fuel to produce thermal energy for various needs. This paper analyses the operational characteristics of the combined heat and power plant, which has been operating since January 1, 2021, at the Voždovac Heating Plant as part of the Belgrade district heating system. The combined heat and power plant consists of three gas engine units with a total nominal electric power of 10 MW and thermal power of 10.1 MW, which use natural gas as fuel. The combined heat and power plant is used for district heating and preparing domestic hot water while electricity is sold to the local electric grid. The analysis in this paper focuses on the plant's operational characteristics: the number of working hours, the total energy consumption and energy production, the efficiency as well as the operational and maintenance costs. Also, the impact of the drastic changes in the prices of natural gas, electricity, and maintenance costs in the last year on the financial profitability of the combined heat and power plant was analysed in particular. [ABSTRACT FROM AUTHOR]

The district heating system is an important heating mode in the northern cities of China. In recent years, the scale of the district heating system is expanding day by day, the pipe network structure is more and more complex. The problem of hydraulic imbalance of the pipe network is gradually emerging, therefore, it is urgent to establish an accurate and perfect hydraulic simulation model of heating network to assist operation management. Pipe network simulation modeling is one of the important prerequisites to solve the hydraulic imbalance problem of heating pipe network. However, with the increase of service time, the actual resistance coefficient of heating network becomes difficult to obtain, which is one of the key reasons for the low accuracy of pipe network simulation model. In order to overcome this difficulty, this paper proposes to use the resistance coefficient identification model based on the differential evolution algorithm (DEA) to identify the resistance coefficient of the heating pipe network. Based on graph theory, network matrix and the law of conservation of mass, the hydraulic model of the heating pipe network is built, and the nodal pressure method is used to solve the model. On the basis of comprehensive consideration of the mainstream intelligent algorithm, the differential evolution method is selected as the algorithm to identify the resistance coefficient of pipeline. In order to verify the identification effect, the feasibility of the model was verified by calculating the data of three different operating conditions of the practical engineering named "K district heating system". The results demonstrated that the relative errors of the identified resistance coefficients are all within 10, and 98% of the identified values are less than 5%. [ABSTRACT FROM AUTHOR]

This research examines the integration of geological and hydrogeological data in numerical aquifer model simulations, with a particular focus on the urban area of Torino, Italy. The role of groundwater resources in urban sustainability is analysed. The objective is to integrate open-loop geothermal plants into the district heating network of IREN S.p.A. Two case studies are examined: the Torino Nord area and the Moncalieri area, both of which host district heating plants. The work entails the collection and analysis of data from a variety of sources, including geognostic surveys and permeability tests, in order to construct a three-dimensional numerical model of the surface aquifer. Models were built using the public MODFLOW 6 (model of groundwater flow) code and calibrated using PESTHP (High Performance of Model Independent Parameter Estimation and Uncertainty Analysis). Results indicate the potential of urban aquifers as renewable energy sources and the necessity of comprehensive geological and hydrogeological assessments for optimal ground water heat pump (GWHP) system installation. This paper emphasises the significance of sustainable water management in the context of climate change and urbanisation challenges. [ABSTRACT FROM AUTHOR]

The LDR-50 low-temperature nuclear reactor is designed for the Finnish and European district heating markets, as an environmentally sustainable heating option for the 2030s. While the carbon footprint of conventional electricity-producing reactors is known to be small, there have been no comprehensive studies on the emission reduction potential when the technology is applied to the heating sector. This paper aims to fill this knowledge gap by means of life cycle assessment (LCA) analysis. The carbon footprint of the LDR-50 heating plant is evaluated, and compared to conventional heating fuels, direct electric heating, and heat pumps. The results of the analysis show that the life cycle CO2 emissions are low, although there are still significant uncertainties related to the construction phase, due to missing data. In addition to carbon footprint, the analysis is also extended to other adverse environmental impacts. It is concluded that significant reductions in CO2 emissions can be achieved by replacing fossil heating fuels with nuclear energy. The technology is considered a viable option alongside biofuels and heat pumps. The overall environmental impacts are low, and the production does not compete for low-carbon electricity or scarce natural resources. [ABSTRACT FROM AUTHOR]

Renewable energy sources, distributed generation, multi-energy carriers, distributed storage, and low-temperature district heating systems, among others, are demanding a change in the way thermal networks are conceived, understood, and operated. Governments around the world are moving to increase the renewable share in energy distribution networks through legislation like the European Directive 2012/27 in Europe, and solar energy integration into district heating systems is arising as an interesting option to reduce operation costs and carbon footprint. This conveys an important investment that adds complexity to the management of thermal networks and often delays the return on investment due to the unpredictability of renewable energy sources, like solar radiation. To this end, this paper presents an optimisation methodology to aid in the operative control of an existing solar district heating system located in the northwest of France. The modelling of the system, which includes a large-scale solar field, a biomass boiler, a gas boiler, and thermal energy storage, was previously built in Dymola. The optimisation of this network was performed using MATLAB's genetic algorithm (GA) and running the Dymola model as functional mock-up units, FMUs, using Simulink's FMI Kit. The results show that the methodology presented here can reduce the current operation costs and improve the use of the daily storage of the DH system by a combination of mass flow control and the implementation of a flexibility function for the end-users. The cost-per-kWh was reduced by as much as 16% in a single day, and the share of heat supplied by the solar field on this day was increased by 5.22%. [ABSTRACT FROM AUTHOR]

The number of data centres (DC) in recent years is growing rapidly, and with that, the share in total consumption of electricity is growing too. A significant amount of electricity is transformed into heat energy which increases the optimal temperature in DC for component operation. This heat needs to be removed and usually, it doesn't have any further application. Today it is recognized that waste heat can be integrated into district heating (DH) and by using it reduce the usage of conventional heat fuels. Integration of waste heat is possible in three ways: with a heat exchanger (HEX), with a booster heat pump, or with the combination of the HEX and heat pump. In this paper, a combination of HP and HEX was used. Although those utilizations are examined and implemented, there is a lack of research on the optimization of the integration of waste heat into the district heating network (DHN). To perform optimization, a thermodynamic model of the DC and a pinch analysis model were developed. In this study, a method for evaluating the economic feasibility of DC waste heat integration into DH systems is proposed. The most suitable integration technology of waste heat into DH systems by using the hourly merit order of waste heat utilization technologies based on pinch analysis is found. The connection pipe between DC and DHN is optimized, and the ideal diameter is determined considering different temperature regimes of the network: low-temperature, ultralow temperature, and neutral temperature networks. The methodology was tested using a case study of a DC in the City of Zagreb. [ABSTRACT FROM AUTHOR]

District heating will play an important role in the transition towards climate-neutral heating. Various studies on modelling the energy system show that district heating and the related expansion of the networks can have different levels of importance. A main reason is that the costs for distribution grid expansion are not well or not at all considered and empirical evidence for a threshold for cost-effective distribution costs is missing in such studies. In this paper, we aim to improve empirical evidence allowing to improve the representation of future district heating expansion in energy systems models. For that, the current status of district heating is analysed in high spatial resolution for Germany. The results show that with the currently accepted average costs, a large range of the possible future market share of district heating for buildings between 17-52% is possible by 2050, with the parameters of the connection rate and the renovation rate of the building stock. We conclude that the district heating share could be increased by the factor of 2 to 5 in the future, proving the importance of climate-neutral district heating in the transition. [ABSTRACT FROM AUTHOR]

District heating companies utilize smart meters that generate alarms that indicate faults in their sensors and installations. If these alarms are not tended to, the data cannot be trusted, and the applications that utilize them will not perform properly. Currently, smart meter data are mostly used for billing, and the district heating company is obligated to ensure the data quality. Here, retrospective correction of data is possible using the alarms; however, identification of sensor problems earlier can help improve the data quality. This paper is undertaken in collaboration with a district heating company in which not all of these alarms are tended to. This is due to various barriers and misconceptions. A shift in perspective must happen, both to utilize the current alarms more efficiently and to permit the incorporation of predictive capabilities of alarms to enable smart solutions in the future and improve data quality now. This paper proposes a prediction framework for one of the alarms in the customer installation. The framework can predict sensor faults to a high degree with a precision of 88% and a true positive rate of 79% over a prediction horizon of 24 h. The framework uses a modified definition of an alarm and was tested using a selection of machine learning methods with the optimization of hyperparameters and an investigation into prediction horizons. To the best of our knowledge, this is the first instance of such a methodology.

Decarbonising the heating sector is one of the key elements to realizing the ambitious dual carbon goals of China, which is the largest carbon emitter and energy consumer globally. Currently, district heating (DH) systems have penetrated approximately 88% of the urban heating areas in Northern China. Nevertheless, around 90% of the heating demand in China still relies on fossil fuels. A larger scale integration of renewable energy and waste heat sources into the DH systems is critical for decarbonising the entire heating sector in China. However, a deeper level of comprehension is required to harness its full potential. This paper provides a thorough investigation of the status, potential, and national policy schemes of renewable energy and waste heat recovery in the DH systems of China. Combined with a critical review of recent literature on relevant areas published in both international and Chinese domestic sources, the trends, challenges, and future perspectives are discussed from scientific research and practical implementation aspects. This paper highlights the synergy of the integration of renewable energy and waste heat sources in DH, the energy efficiency improvements as well as the use of thermal storage technologies through the implementation of 4th generation district heating and smart energy systems that could offer a more economically viable pathway forward. • Focus on renewable energy and waste heat (REWH) in the district heating (DH) systems in China. • A systematic review of REWH in Chinese DH systems from status, policy, and literature aspects. • Identification of research gaps based on the review of both international and Chinese journals. • Policy recommendations proposed to promote REWH in Chinese DH systems. • The introduction of international experiences on REWH in DH for analysis in the Chinese context. [ABSTRACT FROM AUTHOR]

The energy transition towards sustainable resources is more urgent than ever given the environmental and geopolitical challenges. Being one of the major energy users, cities need to understand their energy sector to accomplish its transition, by means of data. However, data are not easily accessible and have their own challenges. This paper presents a joint effort between researchers, city representatives and industry to provide an urban system service that supports research, accelerates urban innovation, and involves the community. An energy data portal, "NRGYHUB", has been developed, where hourly data from thousands of energy meters are available. These meters were collected from neighborhoods in the city of Västerås, Sweden, and they measure electrical and heating energy. In addition, the data are complemented by geometrical and non-geometrical information of the buildings, as well as demographic statistics of the areas. The paper describes the process of data collection, preprocessing, and visualization, in addition to the main challenges and limitations of the project. This dataset can be used for energy use benchmarking, prediction, and analysis. • The creation and implementation of an energy data portal is detailed and made available on nrgyhub.mdu.se. • Legal and licensing issues in data sharing are explored, offering insights for those interested in Sweden and beyond • By showcasing real-world problems, the impact and role of this data sharing initiative are demonstrated. [ABSTRACT FROM AUTHOR]

• Analysis of 12 decarbonisation scenarios via the electrification of space heating. • Innovative modelling approach that combines two highly detailed models. • Building stock and upstream supply sector of whole EU are covered. • Electrification via heat pumps leads to 11% lower system costs compared to hydrogen. • Heat pumps are cost-efficient in decentralised and in district heating systems. This paper analyses different levels and means of the electrification of space and hot water heating using an explorative modelling approach. The analysis provides guidance to the ongoing discussion on favourable pathways for heating buildings and the role of secondary energy carriers such as hydrogen or synthetic fuels. In total, 12 different scenarios were modelled with decarbonisation pathways until 2050, which cover all 27 member states of the European Union. Two highly detailed optimisation models were combined to cover the building stock and the upstream energy supply sector. The analysis shows that decarbonisation pathways for space and water heating based on large shares of heat pumps have at least 11% lower system costs in 2050 than pathways with large shares of hydrogen or synthetic fuels. This translates into system cost savings of around €70 bn. Heat pumps are cost-efficient in decentralised systems and in centralised district heating systems. Hence, heat pumps should be the favoured option to achieve a cost-optimal solution for heating buildings. Accordingly, the paper makes a novel and significant contribution to understanding suitable and cost-efficient decarbonisation pathways for space and hot water heating via electrification. The results of the paper can provide robust guidance for policymakers. [ABSTRACT FROM AUTHOR]

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. • A semi-decentralized approach for disturbance rejection in district heating grids. • Tuning rules for a filtered Smith predictor with bounded time-delay. • Reduced order model for prediction and parameter scheduling for disturbance rejection. [ABSTRACT FROM AUTHOR]

Fluid flow networks (FFNs) widely exist in industrial energy systems tightly related with the industrial production and residents living, such as district heating networks (DHN), mine-ventilation systems and gas transportation systems. The FFN operation is to drive the flowrates and pressures to their desired values, and the flowrate-pressure coordinated control of FFN is crucial in providing safe, stable and efficient operation. Although fluid capacitance has the same importance as fluid resistance and fluid inductance in giving dynamical characteristics of FFN, fluid capacitance is still not fully considered in the flowrate and pressure control design of FFN. In this paper, a nonlinear dynamic model of general FFN with fluid resistance, inductance and capacitance is first given. By using this nonlinear model, it is shown that the general FFN dynamics is strictly passive, and the corresponding generalized Hamiltonian form (GHF) is also given. Based on the passivity of FFN, a decentralized adaptive flowrate-pressure coordinated control is newly proposed, taking a simple proportional-integral (PI) form while providing globally asymptotic regulation for network flowrates and pressures. This FFN control method is applied to design the flowrate-pressure controller of an auxiliary startup circuit (ASC) equipped to a modular high temperature gas-cooled reactor (mHTGR), and simulation results in the cases of heating-up and cooling-down show the feasibility of control design. • A nonlinear dynamic model is given for fluid flow networks with capacitance. • The dynamics of fluid flow networks is shown to be strictly passive. • A decentralized adaptive pressure-flowrate coordinated control is proposed. • Application to the startup of a nuclear reactor is given. [ABSTRACT FROM AUTHOR]

With increasing volatility in natural gas markets and the need for residential heat, research for alternative thermal systems based on green hydrogen-based fuels is necessary. Massive implementation of hydrogen in the current fleet presents a challenge for the decarbonisation of conventional thermal processes. This paper presents the integration of green methanol from a seasonal thermochemical energy storage system (TCES) coupled with district heating networks (DHN). It allows for a solar-based storage and low-temperature heat generation from the exothermic discharge reaction. The system uses concentrated solar thermal energy to decompose methanol into syngas at moderate temperatures (<315 °C), reducing GHG emissions from combustion to meet residential heat. Its potential is assessed through an analysis of 458 rural municipalities in Spain, achieving a substitution of 3.1 % of the natural gas demand. The system allows the production of green fuels from syngas using an open-loop approach, offering new market pathways in primary sector. In a closed-loop configuration, roundtrip efficiencies exceeding 60 % and chemical conversion efficiencies exceeding 70 % are reached, resulting in a global efficiency of 12 % for the DHN and methanol-TCES. The results show a levelized cost of stored energy highly competitive with other storage systems (<200€/MWh), given its simplicity. • A novel district heating network integration with methanol TCES is proposed. • Round-trip above 65 % and an overall efficiency of 11.6 % were achieved. • Analysis of presented DH-TCES in 499 rural municipalities in Spain. • Competitive levelized storage price values of €150/MWh was obtained. [ABSTRACT FROM AUTHOR]

Network temperatures in district heating systems are important operational factors for obtaining efficient performance. A low network return temperature allows for the recovery of low-grade heat from assets such as condensing boilers, waste incineration, geothermal sources and industrial waste heat. Fluctuations in heating and cooling demands affect the return temperatures of the building substations and in the network. This variability impacts the economic viability and environmental sustainability of the entire system. This paper presents a nonlinear optimization strategy to maintain sufficient energy flows in the network's primary and secondary circuits to achieve low return temperatures from all substations in the network. The defined optimization strategy incorporates the thermodynamic model of the substation and building heating system as opposed to traditional weather-based supply temperature adjustments. The estimated heat demands and tariffs, ▪ penalties are inputs used by the optimizer to find the optimal solution. The total operational expenditure for electricity and gas consumption shows an 18% reduction with 8% reduction in emissions and 6% efficiency improvement when compared with the measured weather-based approach. The developed strategy will aid the network operators in the economic dispatch of heat generation while ensuring the user's thermal comfort. • Achieving low network return temperature by optimizing energy flows at district heating substations. • Maintaining the primary and secondary sides mass flows by introducing the new factor. • Finding optimal network temperatures and flow rates by estimating energy demands of the buildings. • Improved network techno-economical and environmental performance and thermal comfort of consumer. [ABSTRACT FROM AUTHOR]

• A pre-1919 primary school with single glazing in Edinburgh has an oversizing of its space heating system of 32 % at design conditions. • Supply temperature can be operated below 70 °C all year round. • Supply temperatures can be reduced below 55 °C all year-round during daytime. As part of the decarbonization of its existing building stock the UK needs to replace gas boilers with heat pumps and low-temperature heat networks. Both technologies are efficient at supply temperatures of 55 °C, with a maximum of 70 °C for heat networks, when existing systems have been designed to operate at 82 °C. Most space heating systems are expected oversized and operate most of the year in part-load, which facilitate the temperature reduction, but little is known about the degree of oversizing. This paper uses the case study of a pre-1919 school in Edinburgh to evaluate the true oversizing of its heating system and its consequences on minimum supply temperatures. This building is still equipped with single glazing and is therefore a worst-case scenario. An oversizing of 32 % was estimated which enables the use of a supply temperature below 70 °C all year round. Moreover, the supply temperature can be kept below 55 °C all year round during daytime due to internal heat gains. In conclusion, this building shows a nascent readiness for low-temperature heat. It would benefit from energy efficiency measures such as double-glazed windows, but this is not pre-requisite. Those results are important for the heat network industry when sizing their systems, but also energy and asset managers when they schedule renovation programmes to have their buildings low-temperature-ready. [ABSTRACT FROM AUTHOR]

• Efficient operating range of the original district heating substation is below 1℃. • Proposed system formed by original components operates efficiently in whole winter. • Control strategies are based on the lowest primary return water temperature. • The proposed system has advantages in energy and economic performance. With the rapid development of heating technology, heating terminals are developing toward low temperatures and diversification, resulting in the simultaneous presence of different temperature demands in district heating systems. To reduce the primary return water temperature and satisfy the temperatures of different terminals, a dual-temperature district heating substation supplying dual temperatures of hot water with two absorption heat pumps and two heat exchangers has been proposed based on the design conditions. However, whether the dual-temperature district heating substation can operate and how to control this system during the entire heating period have not been explored. In this paper, the models for the substation with two absorption heat pumps and two heat exchangers and its subsystems were established to analyze and compare the operational conditions for the substation and its subsystems at different outdoor temperatures. By comparing the primary return water temperatures of all subsystems, control strategies and a combined system for efficient operation during the heating season were determined. Then a case study and analysis of the combined system were conducted under the proposed control strategies and compared with two other systems – two heat exchangers and two absorption heat exchangers – used in dual-temperature heating stations. Results show that 1) The original system with two absorption heat pumps and two heat exchangers could only operate when the outdoor temperature was −8–1℃. 2) The subsystem with a high-temperature absorption heat pump and two heat exchangers and the subsystem with two heat exchangers which could achieve efficient operation under outdoor temperature ranges of 1–7 °C and 7–11 °C respectively were considered in the combined system to broaden the operating range of the original system. 3) The combined system had the lowest return water temperature (23.8℃) and the highest coefficient of performance (6.60) during the entire heating season. The payback period of the combined system was 1.54 years. This study provides a reference for the efficient operation of dual-temperature district heating substations at different ambient temperatures during the heating season. [ABSTRACT FROM AUTHOR]

• A new platform for the integrated assessment of waste heat recovery is presented. • The platform assesses physical, techno-economic, market and business dimensions. • The platform achieves robust results within a short time-frame. • The new platform aims to help untapping the large waste heat potential. At a time when European countries try to cope with escalating energy prices while decarbonizing their economies, waste heat recovery and reuse arises as part of the solution for sustainable energy transitions. The lack of appropriate assessment tools has been pointed out as one of the main barriers to the wider deployment of waste heat recovery projects and as a reason why its potential remains largely untapped. The EMB3Rs platform emerges as an online, open-source, comprehensive and novel tool that provides an integrated assessment of different types of waste heat recovery solutions, (e.g. internal or external) and comprises several analysis dimensions (e.g. physical, geographical, technical, market, and business models). It has been developed together with stakeholders, and tested in a number of representative contexts, covering both industrial and heat network applications. This has demonstrated the enormous potential of the tool in dealing with complex simulations, while delivering accurate results within a significantly lower time-frame than traditional analysis. The EMB3Rs tool removes important barriers such as analysis costs, time and complexity for the user, and aims at supporting a wider investment in waste heat recovery and reuse by providing an integrated estimation of the costs and benefits of such projects. This paper describes the tool and illustrates how it can be applied to help unlock the potential of waste heat recovery across European countries. [ABSTRACT FROM AUTHOR]

This study investigates how differences in energy-related properties of cities influence the composition of a cost-efficient urban energy system, assuming electrification of the transport and industry sectors and zero-emission of CO2. These differences are evaluated for two scenarios regarding the capacities of the modeled cities to import electricity. A linear optimization model that encompasses the electricity, heating, industry, and transport sectors, using measured data from six cities in Sweden, is applied. Results show that when strict constraints on electricity imports are enforced, cities with a lower ratio of annual electricity demand for heat encourage the implementation of power-to-heat solutions in the heating sector. This study also reveals that under such stringent electricity import conditions, cities with a high level of flexibility in electricity demand favor a combination of batteries and solar photovoltaics as opposed to biomass-based electricity production. Conversely, when electricity importation is less restricted and biomass prices surpass 20 EUR/MWh, local electricity generation is outcompeted by imports, and large-scale heat pumps working in tandem with thermal energy storage dominate the heating sector in all modeled cities. This assertion holds true when the maximum electricity import capacity is utilized up to 5000 h annually. [ABSTRACT FROM AUTHOR]

This feasibility study investigates extracting thermal energy from the Bedretto tunnel in the Swiss Alps, which benefits from subsurface heat flux and rock overburden insulation. Using the simulation software COMSOL Multiphysics, we created a numerical model of the tunnel environment to evaluate which medium between rock, air, and water serves as the most effective heat source. Our findings indicate that flowing water is the most effective heat source. Potential applications include distributing the water to nearby villages and storing remaining heat in the subsurface. Estimates indicate that the total extractable thermal energy ranges between 0.8 MWth and 1.5 MWth after reducing the water temperature to 4 °C via a heat pump. The study identifies the most suitable energy sourcing locations based on efficiency and investment costs. Circulating water to individual heat pumps in Bedretto, with the natural elevation difference, enables water transport without a pump. Cost analyses reveal that the investment in piping and heat pumps can be amortized within the equipment's lifespan with appropriate economic models. With the same initial investments, district heating systems are viable in villages with over 30 connections. The payback periods are 10 years for 60 connections, 4.5 years for 90 connections, and immediate for 200 connections. [ABSTRACT FROM AUTHOR]

Thermochemical energy storage (TCES) presents a promising method for energy storage due to its high storage density and capacity for long-term storage. A combination of TCES and district heating networks exhibits an appealing alternative to natural gas boilers, particularly through the utilisation of industrial waste heat to achieve the UK government's target of Net Zero by 2050. The most pivotal aspects of TCES design are the selected materials, reactor configuration, and heat transfer efficiency. Among the array of potential reactors, the fluidised bed emerges as a novel solution due to its ability to bypass traditional design limitations; the fluidised nature of these reactors provides high heat transfer coefficients, improved mixing and uniformity, and greater fluid-particle contact. This research endeavours to assess the enhancement of thermochemical fluidised bed systems through material characterisation and development techniques, alongside the optimisation of heat transfer. The analysis underscores the appeal of calcium and magnesium hydroxides for TCES, particularly when providing a buffer between medium-grade waste heat supply and district heat demand. Enhancement techniques such as doping and nanomaterial/composite coating are also explored, which are found to improve agglomeration, flowability, and operating conditions of the hydroxide systems. Furthermore, the optimisation of heat transfer prompted an evaluation of heat exchanger configurations and heat transfer fluids. Helical coil heat exchangers are predominantly favoured over alternative configurations, while various heat transfer fluids are considered advantageous depending on TCES material selection. In particular, water and synthetic liquids are compared according to their thermal efficiencies and performances at elevated operating temperatures. [ABSTRACT FROM AUTHOR]

The main goal of this article is to give an overview of the importance of district heating and specifically emphasize its continued use with alternative fuels in the upcoming post-lignite era. The results of the cost–benefit analysis for district heating in the transition period after show promise and positivity. By examining key aspects undergoing changes and conducting a SWOT analysis related to this shift, this study sheds light on various benefits for the economy, society, and the environment in sustaining district heating post-lignite era. Additionally, it introduces a solution tailored to meet all district heating needs in Western Macedonia, Greece, during both the transitional phase and after phasing out existing lignite units as, per Greek National Energy and Climate Plan requirements. This devised solution ensures comprehensive coverage of all district heating demands. [ABSTRACT FROM AUTHOR]

Historical buildings account for a significant portion of the energy use of today's building stock, and there are usually limited energy saving measures that can be applied due to antiquarian and esthetic restrictions. The purpose of this case study is to evaluate the use of the building structure of a historical stone building as a heating battery, i.e., to periodically store thermal energy in the building's structures without physically changing them. The stored heat is later utilized at times of, e.g., high heat demand, to reduce peaking as well as overall heat supply. With the help of Artificial Intelligence and Convolutional Neural Network Deep Learning Modelling, heat supply to the building is controlled by weather forecasting and a binary calendarization of occupancy for the optimization of energy use and power demand under sustained comfortable indoor temperatures. The study performed indicates substantial savings in total (by approximately 30%) and in peaking energy (by approximately 20% based on daily peak powers) in the studied building and suggests that the method can be applied to other, similar cases. [ABSTRACT FROM AUTHOR]

Considering the fact that the energy sector producing both thermal and electrical energy has a contribution to the increase of greenhouse gas emissions, the need to diversify energy production sources and equipment such as biomass power plants, installations that recover secondary fuel and thermal energy resources, solar installations and heat pumps is a major priority. The study carried out presents a solution for the integration of renewable energy sources (RES) for the production of electricity that will then be used both in the own thermal energy supply facilities, following that the surplus electricity will be used for the production of hot water that can be delivered in the district heating system. [ABSTRACT FROM AUTHOR]

This paper presents the thermoeconomic analysis and optimization of the Erzincan Waste Tire Recycling and Power Plant (EWTRPP) in Turkey and its waste heat-based district heating (DH) system. A thermoeconomical method, namely the specific exergy costing (SPECO), is applied to allocate cost flows through subcomponents of an actual existing plant. Besides, the obtained thermoeconomic results are improved by using an optimization method, namely non-dominant sorting genetic algorithm (NSGA-II), considering the temperature of the exhaust gas discharged to the atmosphere (T 25), the thermal conductivity value of the insulation material (ki) and pipe roughness value (s). The energy and exergy efficiencies of the existing plant are found to be 27.37% and 35.57%, respectively, considering the data of the actual plant. Moreover, the energy and exergy efficiencies of the waste heat-based DH system are found to be 43.08% and 55.99%, respectively. The total cost rate of the overall system is deduced 13.98 $/hby means of SPECO method. According to the results of the NSGA-II optimization method, the exergy efficiency and total cost rate of the overall system are evaluated as 6.93% and −2.51 $/h, respectively. Furthermore, it is also proposed that 1304 dwellings can be heated owing to the DH system utilizing the existing exhaust gas. • Thermoeconomic analysis and optimization of a waste tire recycling and power plant. • Specific exergy costing (SPECO) and optimization (NSGA-II) analyses. • Waste heat-based district heating system. [ABSTRACT FROM AUTHOR]

To facilitate the ongoing transition to fourth-generation district heating systems, it is necessary to find resource-efficient methods to model the differential pressure in a district heating network accurately. This paper has developed, tested, and compared data-driven methods to create a soft sensor for a pressure transmitter in the district heating network. The sensor is used to control the district heating load and therefore, is the most critical spot of the sensor network. The data-based modelling approaches chosen were transfer functions and neural networks. The data set was collected from Hafslund Oslo Celsio's historical database for January–March 2021, when the heating demand is highest. The best convolutional neural network and a first-order transfer function give acceptable results in estimating the pressure transmitter signal. Both models have the simplest architectures within their model type, suggesting that the need for complex models in either approach is redundant. [Display omitted] • Modelling approaches in deriving a soft sensor for the differential pressure in a district heating system. • Full description of the process of deriving a purely data-driven model for a pressure transmitter soft sensor. • Presents a soft sensor for a pressure transmitter with an accuracy of 0.018 (Convolutional Neural Network) and 0.021 (System Identification). [ABSTRACT FROM AUTHOR]

District heating can play a decisive role in the transformation to a climate-neutral building sector, replacing fossil fuels. Renewable and excess heat potentials for district heating are often spatially limited and a consistent EU-wide analysis of the potentials is not yet available. In this paper, we quantify the renewable and excess heat potentials that could supply future district heating areas for the entire EU. We combine different data sets with a high spatial resolution and conduct spatial matching. Subsequently, we cluster the results for the potentials for individual district heating areas to derive representative types. The results show that the renewable and excess heat potentials together with heat pumps are overall sufficient to supply the future district heating demand, with high technical potentials from geothermal heat and excess heat from wastewater treatment plants. Decreasing the system temperatures increases the amount of available potentials. Lower heat densities and the overall character of the future supply sources require a paradigm shift in DH systems. Large central CHP units will need to be replaced by a diversity of several smaller sources, often combined with heat pumps and utilized at lower system temperatures. [Display omitted] • Regional data on technical renewable and excess heat potentials for district heating in a climate-neutral energy system. • Spatial matching of potentials to district heating areas. • Clustering into DH types for better assessment of country-specific potentials and recommendations. • Ambitious district heating market shares can be supplied by renewable and excess heat potentials in the future. [ABSTRACT FROM AUTHOR]

This paper develops a computationally fast algorithm to disaggregate the total energy use recorded by smart heat meters into space heating (SH) and domestic hot water (DHW). The algorithm trains a regression model on SH-only hours and predicts SH for all other hours with potential DHW use. Data from smart water meters were used to identify hours with only SH. Assessing 13 regression models, an untuned random forest was identified as the best-performing regression model with an acceptable computational cost (median: 7.4 s per building). Furthermore, using one year of data from over 2400 single-family homes, it was shown that the best result (median CVRMSE: 0.13) can be obtained using only smart heat meters based regressors, increasing the applicability of the developed method. Furthermore, two tests were implemented, and it was successfully demonstrated that they identify situations where the regressors are distributed differently for hours with SH only and hours with SH and DHW, to identify possible training bias; thus, buildings where the disaggregation is potentially unreliable. Validation against data from three single-family houses with known SH and DHW use confirmed the good performance of the method and that the performance can be estimated without ground truth data via nested cross-validation. [Display omitted] • Calculation of space heating (SH) and domestic hot water (DHW) from total energy use. • Requires only hourly data from smart heat and water meters; is computationally fast. • Developed using one year's data from over 2400 single-family houses. • Method validated against ground truth data from 3 single family houses. • Accuracy estimate can be obtained without labelled known data. [ABSTRACT FROM AUTHOR]

The technical and economic aspects of a district heating system coupled with a deep open-loop geothermal well (DOLGW) and heat pumps were studied in the paper. A typical configuration of such a geothermal district heating system was proposed, and the corresponding thermal analysis was carried out. Based on the data from the DOLGW heat extraction test conducted in Hebei, China, the optimal size selections of heat pumps, plate heat exchangers, and terminal heat radiators for such a system was analyzed theoretically. In addition, an optimal control scheme for such a system with the change of environmental temperature or heating load were given. [ABSTRACT FROM AUTHOR]

Seasonal thermal energy storage (STES) allows storing heat for long-term and thus promotes the shifting of waste heat resources from summer to winter to decarbonize the district heating (DH) systems. Despite being a promising solution for sustainable energy system, large-scale STES for urban regions is lacking due to the relatively high initial investment and extensive land use. To close the gap, this study assesses the potentials of using two naturally available structures for STES, namely valley and ground pit sites. Based on geographical information system (GIS) methods, the available locations are searched from digital elevation model and selected considering several criteria from land uses and construction difficulties. The costs of dams to impound the reservoir and the yielded storage capacities are then quantified to guide the choice of suitable sites. The assessment is conducted for the northern China where DH systems and significant seasonal differences of energy demand exist. In total, 2,273 valley sites and 75 ground pit sites are finally identified with the energy storage capacity of 15.2 billion GJ, which is much larger than the existing DH demand in northern China. The results also prove that 682 valley sites can be achieved with a dam cost lower than 20 CNY/m3. By conducting sensitivity analysis on the design dam wall height and elevations, the choices of available natural structures are expanded but practical issues about water pressures and constructions are also found. Furthermore, the identified sites are geographically mapped with nearest urban regions to reveal their roles in the DH systems. In general, 560 urban regions are found with potential STES units and most of them have STES storage capacities larger than their own DH demand. The novel planning methodology of this study and publicly available datasets create possibilities for the implementations of large-scale STES in urban DH systems. [ABSTRACT FROM AUTHOR]

Accurate heat load prediction is the key to achieve fine control, energy conservation, and carbon reduction of regional hydronics. Taking the regional hydronics of a city in the north of China as the research object, the author, respectively uses back propagation neural network (BPNN), genetic algorithm (GA) optimized BPNN (GA-BPNN), and autoregressive integrated moving average model (ARIMA) combined BPNN (ARIMA BPNN) to predict its heat load, and compares the accuracy and applicability of each prediction method. The results indicate that GA-BPNN has the smallest prediction error, followed by ARIMA-BPNN, but the latter requires less data for prediction. In practical engineering, if there is a sufficient amount of data related to heat load, it is recommended to use GA-BPNN. If there is a small amount of data, ARIMA-BP prediction method can be used. [ABSTRACT FROM AUTHOR]

In the context of the acceleration of the need to store and process data and digital telecommunications, which leads to an increase in global electricity consumption and greenhouse gas emissions, the need for research to find reliable, efficient, and cost-effective solutions to reduce energy consumption and the recovery of the residual heat produced by the data centres is an increasingly urgent one. The article presents aspects that refer to the recovery of residual energy from data centres and its use for the preparation of domestic hot water, but also for the preparation of the thermal agent necessary for heating installations in buildings and respectively modern heating systems, with the mention that the latter work at a low temperature regime. [ABSTRACT FROM AUTHOR]

• Experimental campaign performed to test the operation of a return-to-supply bidirectional substation. • Hardware-in-the-loop technique coupling in real-time realistic thermal load and production profiles. • Detailed tests for representative days, three case studies and extended assessment for the entire year. • Daily district heating contribution ranging between 21% and 100%. • Yearly local production contribution reaches 100% of the user's load, considering the net-metering. The regulatory European and national policies outline the role of efficient district heating in achieving mid and long-term decarbonization targets. Prosumers could be equipped with bidirectional exchange substations to increase the local production contribution. The present paper evaluates the contribution of a bidirectional substation in maximizing the use of thermal energy produced locally by renewable sources or waste heat in a densely populated area, considering the limitation due to the non-contemporaneity of production and consumption and possibilities to overcome them. The substation prototype and the control system were tested in operational conditions, assuming the district heating network operating at two temperature levels (80 °C/50 °C and 60 °C/30 °C for supply and return) and applying the hardware-in-the-loop technique for coupling the substation in real-time with data-driven thermal loads (multi-family residential building) and production (solar panels and waste heat) profiles. The various energy flows in the substation are presented for representative days, resulting in a district heating contribution to the user's load ranging between 99.8 % (winter day) and 21.8 % (summer day). The net-metering mechanism was considered, and the assessment extended to the entire year. The local production contribution to the user's load ranges between 24 % and 100 %, depending on the system configuration considered. [ABSTRACT FROM AUTHOR]

Integration of renewable and waste energy sources, decentralisation, electrification and energy storage, are key pillars of energy transition in the district heating sector. Such a strategy can be implemented at the building level using the multi-carrier energy hub concept, which has recently gained popularity. This paper presents a technical and financial feasibility study of a building-integrated multi-carrier energy hub concept. The case study is performed for an existing large medical centre, where demand occurs simultaneously for electricity, cold, and heat at different temperature levels, including hot process water and steam. The central idea is to replace the high-exergy steam with heat from the municipal district heating network. The concept also includes the integration of heating and cooling loads, heat storage and implementation of an on-site photovoltaic (PV) power plant. The key components of the proposed hub technological structure are high-temperature heat pumps. Five alternative structures of the system configuration are examined using an hour-by-hour annual simulation. The results reveal that the proposed multi-carrier energy hub is fully operational. The project is also profitable, which results mainly from significant energy savings compared to the existing heat supply system using high-pressure steam. However, the profitability strongly depends on the system configuration, and the choice of the best option is ambiguous. The system with heat storage reaches the highest net present value (NPV) while the one without the storage results in the highest internal rate of return (IRR) due to significantly lower capital expenditures (CAPEX). In all cases, the project leads to a considerable cumulative CO 2 emissions reduction, which is at the level of 1351 up to 2961 tons annually depending on system configuration. • Multi-carrier energy hub concept is proposed for a large medical centre. • Heating loads are integrated with district heating network using high-temperature heat pumps. • Cooling and heating loads are integrated using high-temperature heat pumps. • Hour-by-hour simulation of the system including photovoltaic installation is performed. • Technical and financial feasibility of the energy hub system is demonstrated. [ABSTRACT FROM AUTHOR]

The decentralization of energy production and recovery of excess heat (EH) to reach climate targets is essential for renewable and fully decarbonized heating systems. This paper identifies current and potential industrial EH sources providing baseload capacity for district heating (DH) systems. These sources are evaluated by sector and process for supplying baseload capacities explored for current 3rd generation district heating (3GDH) and 4th generation district heating (4GDH) systems with lower grid temperatures and losses, with and without expansions. The method combines geographical analysis and available baseload capacity estimations for 360 Danish DH systems scenario-making and an additional sensitivity analysis evaluating baseload capacity full-load hours. It is found that 80 % of Danish DH systems have an unmet baseload capacity of 50 % or higher. Half of the systems have geothermal capacity available and up to 20 % of industrial EH baseload capacity potential, which sums up to 5 PJ of EH potential within a 2 km distance. The findings also suggest that there is an additional opportunity for the placement of future energy infrastructure able to supply EH, which is highly contextual and strategic in heat planning, particularly considering the future development of sustainable and energy-efficient DH systems. • Maps 360 Danish DH systems with expansion potentials for 3GDH and 4GDH. • Identifies 9235 sources and 19.8 PJ of exploitable industrial excess heat. • Spatially evaluates 3 PJ and 5 PJ of EH for supplying 3GDH and 4GDH baseload capacity. • Locates 5–10 GW of total available baseload capacity in Danish DH systems. • Provides placement opportunities for future excess heat sources. [ABSTRACT FROM AUTHOR]

In future smart thermal grids, decentralized prosumers shall supply each other over the network, optimized by an overarching management system. For this, the substation control must be able to directly process optimal power flow setpoints from the management, while considering the mutual influence of prosumers on the technical level. Addressing these requirements, this paper develops a control approach for bidirectional prosumer substations. Therefore, we identify the objectives and characteristics of the control problem, before relaxing it by reformulation. This enables to keep proportional–integral–derivative controllers (PIDs) for operating the pumps and valves as decentral actuators in the substations. We propose a control approach, exploring the combination of two key aspects: (1) The assignment of temperature objectives to actuators. (2) Weighted error functions that linearly combine temperature and power errors as input for the PIDs, allowing to handle multiple objectives with limited actuators. Through case studies, we validate the suitability of our proposed objective–actuator assignment and demonstrate the necessity and benefits of the weighted error functions. Like this, we conclude with a control approach for bidirectional prosumer substations that aims for the relevant temperature objectives, directly considers heat transfer setpoints, replicates and exploits the coupling within the network, effectively manages conflicting objectives, copes with prosumer interference, and is pragmatic for real-time operation. Our approach can be transferred to different network concepts, bridging the gap between decentralized field-level operation and the management level. • Develop control approach for bidirectional substations in thermal prosumer networks. • Propose weighted error function approach in combination with PID controllers. • Study suitability of different objective-to-actuator assignments for substations. • Bridge management and field level by processing power setpoints in substation. • Anticipate mutual influence of prosumers over the network on the technical level. [ABSTRACT FROM AUTHOR]

As demand for data centers (DC) has increased rapidly, so has their electricity consumption. Cooling DCs is essential to maintain optimal temperatures for the operation of servers and equipment. The consequence of the cooling process is that most of the electricity consumed in DCs, including cooling, is eventually dissipated as heat that is released into the atmosphere without any useful application. Recovering and reusing waste heat offers a sustainable solution to reduce primary energy consumption and minimize the environmental impact. Using waste heat from DCs to heat buildings can significantly improve the energy efficiency and environmental sustainability of DCs. Therefore, this research analyzes the existing potential of waste heat recovery from data centers in Latvia and proposes a system dynamic modelling approach for evaluation of the future impact of waste heat on the national heat supply. The overall waste heat generated by DCs in 2022 was 51.37 GWh at a temperature of 65 °C. By 2050, the total heat energy production potential from DCs will increase to 257 GWh, with 201 GWh being utilized. [ABSTRACT FROM AUTHOR]

Background: Compared to other sectors, the building sector is seriously lagging in efforts to mitigate climate change. In particular, heat provision needs to move to low-carbon options at greater speed. Municipalities are essential players in the transition to low-carbon heating. However, little is known about their experiences in developing heat provision infrastructure and their expectations of low-carbon options, such as district heating based on renewable energy. To explore how the experiences and expectations of municipalities concerning low-carbon heating are related, we conducted a survey of officers responsible for heating technology in municipal authorities across Germany. The questionnaires were analysed using multiple quantitative data analysis techniques. Results: Our findings suggest that officers in larger municipalities have more positive expectations of low-carbon heating technologies than those in smaller and medium-sized municipalities. They also have more experience with these technologies. We identified four different clusters of municipalities based on their attitudes towards heating systems. The findings suggest that attitudes and experiences have a significant influence on the desirability and expected feasibility of the expansion of district heating. Furthermore, there are differences between south, north, and east Germany. Conclusions: Exchange of experiences and expectations between larger and smaller municipalities could facilitate the transition to low-carbon heating. Public policy could strategically provide spaces for the required exchange, but it also needs to engage with more complex questions of finance and regulation. [ABSTRACT FROM AUTHOR]

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The LDR-50 low-temperature nuclear reactor is designed for the Finnish and European district heating markets, as an environmentally sustainable heating option for the 2030s. While the carbon footprint of conventional electricity-producing reactors is known to be small, there have been no comprehensive studies on the emission reduction potential when the technology is applied to the heating sector. This paper aims to fill this knowledge gap by means of life cycle assessment (LCA) analysis. The carbon footprint of the LDR-50 heating plant is evaluated, and compared to conventional heating fuels, direct electric heating, and heat pumps. The results of the analysis show that the life cycle CO2 emissions are low, although there are still significant uncertainties related to the construction phase, due to missing data. In addition to carbon footprint, the analysis is also extended to other adverse environmental impacts. It is concluded that significant reductions in CO2 emissions can be achieved by replacing fossil heating fuels with nuclear energy. The technology is considered a viable option alongside biofuels and heat pumps. The overall environmental impacts are low, and the production does not compete for low-carbon electricity or scarce natural resources.