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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]

The work presented in this paper relates to a small scale district heating network heated by a gas-fired CHP. In most common situations, such a CHP is heat driven operated, meaning that the CHP will switch on whenever heat is needed, while not taking into account the demand of electricity at that time. In this paper however, an active control strategy is developed, aiming to maximize the profit of the CHP, selling its electricity on the spot market. The CHP will therefore switch on at moments of high electricity prices. Nevertheless, since there never is a perfect match between the demand of heat and the demand of electricity, thermal energy storage is included in the network to overcome this difference. Here, three different storage concepts are compared: (1) a central buffer tank next to the CHP; (2) small storage vessels distributed over the different connected buildings; and (3) the use of the thermal mass of the buildings as storage capacity. Besides the development of the control algorithms based on model predictive control, a simulation model of the network is described to evaluate the performance of the different storage concept during a representative winter week. The results show that the presented control algorithm can significantly influence the heat demand profile of the connected buildings. As a result, active control of the CHP can drastically increase the profit of the CHP. The concept with the distributed buffers gives the best results, whereas the profit for the thermal mass concept is only marginally smaller. Since in this latter case no significant investment costs are needed, the conclusion for this case study is that the use of thermal mass of buildings for demand side management in district heating systems is very promising. [ABSTRACT FROM AUTHOR]

Countries in Eastern-Europe have similar characteristics due to their common historical and economic backgrounds. A large part of the housing stock has been built during the Soviet era, applying uniform solutions and similar standards, but similarities extend to other periods as well. On the other hand, the differences should also be noted – although the climate is mainly continental, there are significant variations between South and North and between mountainous and flat areas. In this paper, a detailed comparative analysis is presented for Bulgaria, Serbia, Hungary and the Czech Republic. The results are based on the residential building typologies developed within the TABULA/EPISCOPE project co-funded by the Intelligent Energy Europe Programme. Typical building types will be presented, covering building structures and systems. Important energy performance indicators are identified and compared, supported by available statistical data about the housing stock. The added value of the paper consists of the analysis of heterogeneous data sources and collecting and comparing the information of the housing stock under a common comparison framework of building typology data between countries, and the contribution in the harmonization of the building typology approach. [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]

Numerous cost-optimal studies have been undertaken by EU member states to define minimum energy performance requirements for buildings within that member state in accordance with the Energy Performance of Buildings Directive. As few of these studies have examined the effect of heating and ventilation system parameters on life cycle cost (LCC) and energy use in detail, this paper analysed 84 HVAC solution-sets, including parameters for the heating supply system, heating distribution system and ventilation system, for a case study in Norway. The choice of heating supply system was the dominant parameter, with ground source heat pump solutions offering the lowest purchased energy use and LCC. Electric water heating and district heating systems had low capital costs which make these options more attractive to property developers looking for a good return on investment. Using an exhaust ventilation system with an exhaust air heat pump lowered LCC and capital costs for ground source heat pump and district heating systems but does not meet current Norwegian energy regulations. Despite using more energy, a constant setpoint schedule resulted in a lower LCC than a variable setpoint system due to the variation in hourly energy pricing and the dominant role of monthly pricing based on peak load. The choice of yearly heating strategy and heat emitter had a relatively small impact on energy use, capital cost and LCC. With all the parameters combined, there was variation within each heating system of up to 21 kWh/(m2∙year) in energy use, 78 Euro/m2 in capital cost and 236 Euro/m2 in LCC. Therefore, it is important that such system parameters are considered in cost-optimal assessments to give a fair comparison of HVAC systems. [ABSTRACT FROM AUTHOR]

[Display omitted] This paper introduces a non-linear grey-box (GB) model based on stochastic differential equations that describes the heat dynamics of a school building in Denmark, equipped with a water-based heating system. The building is connected to a local district heating network through a heat exchanger. The heat is delivered to the rooms mainly through radiators and partially through a ventilation system. A monitoring system based on IoT sensors provides data on indoor climate in the rooms and on the heat load of the building. Using this data, we estimate unknown states and parameters of a model of the building's heating system using the maximum likelihood method. Important novelties of this paper include models of the water flow in the circuit and the state of the valves in the radiator thermostats. The non-linear model accurately predicts the indoor air temperature, return water temperature and heat load. The ideas behind the model lay a foundation for GB models of buildings that use different kinds of water-based heating systems such as air-to-water/water-to-water heat pumps. Such GB models enable model predictive control to control e.g. the indoor air climate or provide flexibility services. [ABSTRACT FROM AUTHOR]

The energy demand for supplying Domestic Hot Water (DHW) has an important share in the overall thermal energy consumption of commercial buildings. The aim of this paper is to analyze the performance of DHW production in commercial public service, i.e., educational buildings, to subsequently identify frequent inherent shortcomings of centralised DHW installations and to provide measures for optimization or economically more viable solutions. Several buildings of the University of Natural Resources and Life Sciences in Vienna have been investigated in terms of DHW consumption and performance of the installed centralised systems. Referring to the investigated university buildings, it can be stated, that in cases of low to medium consumption figures, typical centralized DHW installations with a hot water circulation pipework achieve only poor efficiencies in the range of 2–12%. As for one particular centralized DHW system in operation, focusing on demand controlled DHW supply through adapted flow control, e.g., reducing the runtime of the circulating pumps at specific time intervals, and, if applicable and feasible, decreasing hot water flow- and storage capacities can reduce annual energy consumption for DHW by 15–25% and improve the overall system efficiency significantly as could be evaluated in a detailed case study. A seemingly economical yet ecologically controversial option for improving centralised DHW systems is the partial or complete conversion to electric point-of-use water heaters. This reduces thermal energy losses almost completely, hereby significantly increasing the efficiency of a DHW supply system. Nevertheless, existing hot water supply systems, energized by district heating, usually consume less primary energy and most likely generate fewer CO 2 emissions compared to electric DHW heaters. [ABSTRACT FROM AUTHOR]

The logical diagram of method structure in this paper. [Display omitted] In this paper, the demand response of district heating for swimming pools and pool space air is proposed and applied in a swimming hall in Finland. Swimming halls have significant heat demands e.g., domestic hot water supply, space heating and pool water heating, and thus have much large heat storage capacity for the realization of district-heat based demand response. A dynamic building simulation tool IDA ICE was used to simulate whole swimming hall including pools and HVAC systems. In addition, a rule-based demand response algorithm which utilized dynamic district heat price was proposed and applied in the district heating control of the studied swimming hall. The results show that the large storing capacity of pool water promises the large amount of charged and discharged heat energy, and ensure the application of demand response of district heating in swimming hall. The application of demand response of district heating can increase the average pool water temperature from the normal setpoint of 26.5 °C to 27.3 °C. In addition, demand-response district heating control for the swimming pool water and pool space air decreases the total district heat costs of the swimming hall by 1.1%. During the repayment periods of 7 and 15 years, the energy cost savings and maximum cost of profitable investment for the demand response control are between 10 000 € and 20 000 €. [ABSTRACT FROM AUTHOR]

• A well-functioning space heating system can operate below 70 °C for 98% of the year and below 55 °C for 71% of the year. • The performance gap between measured and calculated energy use is widening across building age groups, with a clear increase for post-1980 buildings. • Pre-1980 buildings can operate with supply temperatures below 70 °C for 96–99% of the year and below 55 °C for 67–71% of the year. • Building envelope improvement, whilst recommended, is not a pre-requisite for using low-temperature supply in pre-1980 buildings. • Post-1980 buildings could have limitations in respect of using low-temperature heat under windy conditions. Decarbonising heat in the UK by 2050 will require the wider adoption of low-temperature heat. Current systems, largely relying on gas boilers, have design operating temperatures of 82/71 °C (supply/return) while new standards for 4th Generation District Heating are 55/25 °C. Local authorities must set-up strategies to get their buildings "Heat network ready" but this raises the question of the ability for existing buildings to use low-temperature heat. The aim and the novelty of this paper is to establish a relationship between an energy 'performance gap' in Scottish public buildings and their ability to use low-temperature heat. This performance gap has been evaluated for 121 non-domestic buildings, primarily schools, operated by The City of Edinburgh Council. Space heating system are assumed oversized by 10%. The results show that renovation of the building envelope, while highly desirable, is not a pre-requisite for using low-temperature heat in pre-1980 constructed buildings, which represent 64% of the stock. It also highlights that post-1980 buildings, predominantly utilising mechanical ventilation systems, demonstrate an increasing performance gap which could limit their ability to use reduced operating temperature, especially in windy conditions. [ABSTRACT FROM AUTHOR]

The industrial exhaust flue gas contains tremendous waste heat that cannot be efficiently recovered by conventional condensing heat exchanger. This paper proposes a novel full-open absorption heat pump for the total heat recovery of flue gas. The recovered heat is used for district heating. By applying direct-contact heat and mass transfer without solid transfer interfaces, the novel system can save considerable metallic tube or plate materials and therefore the initial investment can be reduced substantially. A prototype full-open absorption heat pump is developed and tested, achieving the COP (coefficient of performance) of 1.621 and the exit flue gas dew point of 36.2   °C at most. A detailed theoretical model in Eulerian–Lagrangian formulation is established, involving in conjugate heat and mass transfer and particle dynamics. The numerical simulation agrees well with the experiment results. On the basis of the validated model, three critical parameters, including excess air coefficient of the burner, moisture content of the objective flue gas and return water temperature of the district heating network, are selected to study their effects on system performances. As a controlled variable, especially, the excess air coefficient plays an important role by influencing the regeneration of the liquid absorbent in the generator. The full-open absorption heat pump outperforms the condensing heat exchanger by 19.7–178.1% in heat recovery capacity as the return water temperature increases from 40 to 55   °C. [ABSTRACT FROM AUTHOR]

The use of heat pumps in district heating is one of the most promising technologies for enhancing the efficiency of systems and for meeting the 2030 and 2050 European energy and climate targets. It is essential to assess the available data, the practice and experience of planners and engineers to determine heat pump placement, connection and operational modes in district heating networks, as the systems ought to be capable of covering residential heat requirements for all year around operation. The main selection criteria for the appropriate heat pump system are the heat source, the heat pump technology and the heat requirements. These parameters form a technical triangle, which should be used as a comprehensive instrument to enable heat pump integration into residential district heating. The triangle allows the definition of the bidirectional interdependences and the design of a high efficiency, sustainable heat pump based system. This paper presents the solution to scenarios of how to integrate heat pumps into district heating, in terms of heat pump placement, connection and operational modes based on available heat sources and heat requirement profiles and their environmental impact. [ABSTRACT FROM AUTHOR]

Forecasting thermal load is a key component for the majority of optimization solutions for controlling district heating and cooling systems. Recent studies have analysed the results of a number of data-driven methods applied to thermal load forecasting, this paper presents the results of combining a collection of these individual methods in an expert system. The expert system will combine multiple thermal load forecasts in a way that it always tracks the best expert in the system. This solution is tested and validated using a thermal load dataset of 27 months obtained from 10 residential buildings located in Rottne, Sweden together with outdoor temperature information received from a weather forecast service. The expert system is composed of the following data-driven methods: linear regression, extremely randomized trees regression, feed-forward neural network and support vector machine. The results of the proposed solution are compared with the results of the individual methods. [ABSTRACT FROM AUTHOR]

Optimal control of thermostatically controlled loads connected to a district heating network is considered a sequential decision-making problem under uncertainty. The practicality of a direct model-based approach is compromised by two challenges, namely scalability due to the large dimensionality of the problem and the system identification required to identify an accurate model. To help in mitigating these problems, this paper leverages on recent developments in reinforcement learning in combination with a market-based multi-agent system to obtain a scalable solution that obtains a significant performance improvement in a practical learning time. In a first step, all relevant (and practically available) state information is collected from which a limited set of features is extracted, resulting in a low-dimensional representation of the system state. In a second step, a control action for the entire cluster is extracted from a policy determined offline. In a third and final step, this control action is dispatched over the different thermostatically controlled loads using a market-based multi-agent system. This process is repeated following a receding horizon approach. The control approach is applied to a scenario comprising 100 thermostatically controlled loads connected to a radial district heating network supplied by a central combined heat and power plant. Both for an energy arbitrage and a peak shaving objective, the control approach requires 60 days to obtain a performance within 65% of a theoretical lower bound on the cost. [ABSTRACT FROM AUTHOR]

District heating system brings with it the problem of achieving a fair billing service for heating of apartment buildings in the case of uneven temperature in them. The problem is most pronounced when the individual apartments are completely excluded from the heating system of the building. The model of an existing building with 24 apartments was simulated in the software EnergyPlus, for different characteristics of the thermal envelope and different conditions of use, when the apartment with the lowest energy consumption is excluded from the heating system. It was simulated the exclusion of this apartment in which people are present and the lights and electrical appliances are turned on and in which there is no presence of people and electricity consumption (the apartment is empty). As a measure of energy flow between unheated and adjacent apartments, the parameter “stolen” energy is defined. The results of the conducted simulations show that the stolen energy is reduced by the exterior and interior insulation of the building. In this paper, data on energy flow when there is interior insulation in apartments, in particular according to the current regulations in Serbia, are especially analyzed. The results show that, depending on the case and scenario, the stolen energy ranges from 27.23 to 7.97 kWh/m 2 . The insulation of interior walls of the building can significantly mitigate the problem of energy flow due to temperature differences between apartments. [ABSTRACT FROM AUTHOR]

In the planning phase of district energy systems, optimization models based on mathematical programming are a widely used approach. Most optimization models determine the optimal energy system design based on a single representative year. However, this approach is unable to consider changing economic and technological boundary conditions over the system's lifetime. As a result, these one-period models fall short for districts with 5th generation district heating and cooling (5GDHC) networks, which are typically developed over long time periods and are built in multiple construction phases. In this paper, we present two multi-period optimization approaches for designing 5GDHC districts: The first approach is a forward-looking model which determines the optimal investment pathway by using a perfect foresight of future parameter developments. In the second approach, a one-period model is solved repeatedly for every investment period without knowledge of future parameter developments. Both approaches are compared to a one-period model for a real-world 5GDHC district in Germany. In comparison with a one-period design approach, the forward-looking method leads to total cost savings of up to 17 % and the sequential method of up to 11 %. By using a forward-looking model, gas-fired technologies are sized smaller while the capacity of electricity-driven technologies in the energy hub as well as photovoltaic modules and thermal energy storages in buildings increases compared to a one-period model. The case study shows that a multi-period modeling approach is an important addition to design optimization models for 5GDHC networks and can have a significant impact on the optimal design. [ABSTRACT FROM AUTHOR]

• Freely available online overview of district heating efficiency indicators. • Hourly district heating energy use data from approx. 43 000 buildings. • Building stock segmented into building typologies for analysis of: • -1) Heating energy use intensity, 2) load variation and 3) cooling efficiency This paper provides a state-of-the-art and freely available online overview of the district heating (DH) efficiency of Danish building typologies. The overview is based on DH consumption data from 42 969 buildings constructed up until 2017 that in combination with data from the Danish Building and Dwelling Register constitutes a dataset with a previously unseen level of detail, confidence, sample size, and research opportunities. The paper also presents an initial analysis of the dataset in terms of three heating efficiency indicators, namely 1) Annual heating energy use intensity, 2) Daily heat load variation, and 3) Cooling efficiency. The overall finding was that building typologies perform significantly different from one another concerning indicators 1 and 2, but not for indicator 3. It is therefore not possible to declare one building typology more efficient than the other as this depends on the building construction year and the considered efficiency indicator. The data indicate that further energy-efficiency improvements of the existing building stock are essential to the realization of 4th Generation District Heating technologies in Denmark and that these improvements most likely will lead to increased heat load variations that need to be addressed, for instance by enabling a larger degree of demand-side flexibility in the existing district heating systems. The large temporal variation of the buildings' cooling efficiency indicates that there is a potential for rethinking e.g. domestic hot water production in the summer or introduce differentiated billing based on the daily, weekly, or maybe seasonal cooling performance. The presented dataset can be subject to several future investigations which are also discussed in the paper. [ABSTRACT FROM AUTHOR]

Future district heating systems (DHS) will be supplied by renewable sources, most of which are limited in temperature and flow rate. Therefore, operational optimization of DHS is required to maximize the use of renewable sources and minimize (fossil) peak loads. In this paper, we present a robust and fast model-predictive control approach to use the thermal mass of buildings as a daily storage without violating temperature constraints. The novelty of this paper includes two elements. First, the focus on an operational control strategy that explicitly accounts for temperature-limited renewable sources, like a geothermal source. Secondly, the optimization problem is formulated as a (nearly) convex optimization problem, which is required for adoption of model-predictive control in practice. The examples show that the peak heating demand can be reduced by 50%, if the thermal inertia of the buildings is used and the heating setpoints are adapted. Furthermore, the operational optimization finds the proper balance between benefits of pre-heating using renewable sources with limited capacity and costs of additional heat losses due to pre-heating. [ABSTRACT FROM AUTHOR]

Forecasting energy consumption in buildings is a key step towards the realization of optimized energy production, distribution and consumption. This paper presents a data driven approach for analysis and forecast of aggregate space and water thermal load in buildings. The analysis and the forecast models are built using district heating data unobtrusively collected from 10 residential and commercial buildings located in Skellefteå, Sweden. The load forecast models are generated using supervised machine learning techniques, namely, support vector machine, regression tree, feed forward neural network, and multiple linear regression. The model takes the outdoor temperature, historical values of heat load, time factor variables and physical parameters of district heating substations as its input. A performance comparison among the machine learning methods and identification of the importance of models input variables is carried out. The models are evaluated with varying forecast horizons of every hour from 1 up to 48 h. Our results show that support vector machine, feed forward neural network and multiple linear regression are more suitable machine learning methods with lower performance errors than the regression tree. Support vector machine has the least normalized root mean square error of 0.07 for a forecast horizon of 24 h. [ABSTRACT FROM AUTHOR]

The increasing of energy efficiency and decreasing the transportation power consumption of District Heating (DH) systems have been increasingly focused due to the need to save energy. In this paper a new district heating network with distributed variable-frequency speed pumps (DVFSP) is presented and analyzed. The approach for minimum of the capital costs and energy consumption in a district heating network is presented using a case study based on a district heating network with DVFSP in Dalian, China. The computational tool is a commercial software package, which is used to design and analyze DH networks. Increasing temperature difference between supply and return pipes, the annual total electricity consumption and the equivalent annual cost are reduced. The energy efficiency in the DH system with the DVFSP was compared with the one in the DH system with conventional central circulating pump (CCCP). Analysis results show that the average electrical energy saved by the DH system with the DVFSP is 49.41% of the one saved by the DH system with conventional central circulating pump. The average pumps power consumption of heating area per square meter in primary heat supply network is 0.325 kWh/m 2 . [ABSTRACT FROM AUTHOR]

In this paper, the specific consumption of the heat energy supplied by three most utilized heating systems (district heating, gas and electricity system) in the residential sector of the city of Kragujevac (Serbia) is analysed. Required data are provided by combining data from local utility companies with national census results. Comparison of present tariff systems shows that consumers in the residential buildings are the most motivated for energy savings if they use electricity or gas as energy source. The specific energy consumption in district heating system shows relatively high quantities, primarily as a consequence of dominant unmotivating tariff payment system. The average heat consumption from gas and electricity sources relatively fits to EU average, but the electricity consumption of the electric heaters is not acceptable in long term. Low electricity price in Serbia and high price of unit of energy from district heating system of the city of Kragujevac (and Serbia) will lead to an increase of electric energy consumption which will cause additional problems related to covering of that consumption from domestic energy sources. [ABSTRACT FROM AUTHOR]

In this paper, district heating is described and its operation process is considered in varying operation conditions over time. Taking into account the ordered thermal power which affects the amount of heat supply to consumers, the system operation states are introduced. Heat supply to consumers is carried out by means of a heat-carrying agent having the necessary parameters: required quantity, temperature and pressure, in a specific location, under certain operational conditions and timeframe. To model the system operation process and describe the changes between the operation states the semi-Markov process is applied. The identification of the district heating operation process is performed on the basis of real operational data obtained from the District Heating Company in the city of Rzeszow. Using the data and considering the specific character of the system, the main characteristics describing the safety of heat supply to consumers were determined. [ABSTRACT FROM AUTHOR]

With an old mean construction age, Italian buildings are considered as long-lasting goods; 75% and 17% of Italian live respectively in buildings built before 1990 and before 1950. The potential energy savings that can be achieved from the refurbishment of existing dwellings are clearly high. To this regard, the European Directive EPBD recast defines a comparative framework to improve buildings energy performance aiming to the nearly zero energy target by 2020. It is thus important to point out energy retrofit actions to be widely applied to the whole existing buildings stock and to be cost optimal. This paper analyzes the application of space heating control devices such as thermostatic radiators valves (TRVs) on an old existing multi-family building in Turin by means of the EnergyPlus dynamic simulation code. Measured data of the energy supplied by the district heating network were used for calibrating the model. In order to evaluate the impact of the TRVs, simulations were performed with and without TRVs. The application of the dynamic energy simulation to different patterns of TRVs use was proved to bring back significant energy savings from a minimum of 2% up to a maximum of 10%. [ABSTRACT FROM AUTHOR]

This paper describes a computation model using an artificial neural network (ANN) for a thermoeconomic analysis of district heating (DH) mony flows (MF). The model will compute the results of the MFs in accordance with an energy method or a caloric method and an exergy method at various DH substations. A heat distributer is unable to ensure the same quality of heat to all consumers due to the length of the network. A consumer nearest to the heat source receives heat of a higher quality than the last consumer. As the DH heat is usually calculated using the MF energy method, the available heat quantity that can actually be converted into another form of energy is not taken into account in the calculation. The above indicated deviations, however, are taken into consideration in the calculation of heating costs in accordance with the MF exergy method, giving a more realistic picture of the heating cost evaluation. Considering the first law analysis of thermodynamics, the amount of energy consumed is calculated disregarding the difference between work and heat. The analysis and design of engineering systems based on only the first law is not adequate [1] . [ABSTRACT FROM AUTHOR]

The paper examines implementation of heat saving measures in buildings in 2050, under the assumption that heat and power supply comes solely from renewable resources in Denmark. Balmorel – a linear optimisation model of heat and power sectors in Denmark is used for investigating economically viable levels of heat savings, which can be implemented by reducing heat transmission losses through building elements and by installing ventilation systems with heat recovery, in different future Danish heat and power system scenarios. Today almost 50% of heat demand in Denmark is covered by district heating. A further expansion of district heating network in Denmark is assessed and penetration of heat savings is analysed in this context. If all heat saving measures, included in the model, are implemented, heat demand in Danish buildings in 2050 could be reduced by around 40%. Results show that it is cost effective to reduce from approximately 12% to 17% of future heat demand in buildings depending on assumed lifetime and costs of heat saving measures. Individual heating areas have higher penetration of heat savings than district heating areas. When district heating systems are expanded, an overall penetration of heat savings slightly decreases along with lower capacity investments and system costs. [ABSTRACT FROM AUTHOR]

Network hydraulics play a major role in the design and operation stage of District Heating (DH) systems, considering further hydraulic complexities expected in the near future. This paper presents a mathematical solution procedure that computes the network hydraulics, tailored as unique to the principal basis behind the branched type of DH networks. The procedure makes use of simple input data (i.e., pipe-node list) to obtain the mathematical description of the network layout via detection algorithms for the incidence and the loop matrices (the pseudo-code given). The matrix-based solution procedure was formulised to detect the network flow and pressure distributions either by use of the Newton-Raphson or genetic algorithms, based on the conservations of mass and energy. The problem formulation was maintained as correcting the end-user flow rates that satisfy the energy conservation throughout the closed loops of the network, which sped up the convergence to a solution. The developed model was used in a case study consisting of 220 × 2 pipe segments (supply and return) and 214 end-users, the results being obtained in 35.5 s via the Newton-Raphson algorithm. Despite the sensitivity analysis, the genetic algorithm was found to have premature convergences under various trials. [ABSTRACT FROM AUTHOR]

• Three adjusting methods suitable for district heating using ASHPs are proposed. • Energy loss corrections of frosting and on–off are adopted in the simulation model. • Power consumption increment caused by the correction of frosting reaches 3.85–17.41%. • Energy loss ratio of on–off declines from 3.19% to 0.68% with heating area increase. • Energy-saving potential of pump reaches 80.97–86.46% in different adjusting methods. Air source heat pump (ASHP) has been used in Northern China for district heating. However, few investigations on its regulating methods have been conducted till now. To increase the energy-saving effect of AHSPs, a simulation model, which considered the energy loss caused by frosting and on–off, was developed in this paper. Based on this model, three combination regulating modes suitable for district heating using ASHPs as heating source were proposed. Then the heating performance of ASHPs used for district heating in seven cities was investigated using this model. Results showed that both the energy loss corrections of frosting and on–off have evident impacts on the power consumption and seasonal coefficient of performance (SCOP). Owing to the energy loss correction of frosting, the power consumption of ASHP unit is increased by 3.85%–17.41%, and meanwhile SCOP is decreased by 3.72%–14.83%. The influence of the energy loss of on–off decreases gradually with the increase of heating area. In the three regulating modes, the power consumption of ASHP unit changes slightly, while the energy saving rate of water pump can reach 80.97%–86.46%. When the pitch of buried pipe was 300 mm, ASHP can meet the heating demand in all the three regulating modes. [ABSTRACT FROM AUTHOR]

The flexibility of thermal energy systems can support the energy system as a whole in integrating a large share of fluctuating renewable energy sources. The current paper investigates the flexible operation potential of a small district with buildings connected to a district heating network. In the study, the thermal mass of the buildings was utilized as heat storage and the investigation was performed for the heating season. The load shifting scenarios used were created based on the available information on heat load and dynamic heat production cost in the Greater Copenhagen district heating system. The results of the study indicate that the applied strategy of load shifting is highly effective. The achieved load shifting in all schedule-based scenarios was between 41% and 51%. The applied scenarios resulted in an increased peak demand and energy use. However, the increased energy use occurs mostly during the low-load periods, when the heat production prices are lower. It was also shown, that the increased peak can be partially mitigated by using the appropriate control strategies. [ABSTRACT FROM AUTHOR]

• A novel metric (DOC) for bidirectional low temperature networks (BLTNs). • DOC describes the balancing potential of heating and cooling demands in a district. • DOC helps to identify building clusters with complementary demand profiles. • Correlations between DOC and KPIs are elaborated based on 63 demand scenarios. • Performance comparison of BLTNs with state-of-the-art building energy systems. Bidirectional low temperature networks (BLTNs) are a promising technology to drive decarbonization of the heating and cooling sector. The energy efficiency of a BLTN strongly depends on the heating and cooling demands of the connected buildings and their simultaneity. In order to evaluate the efficiency of a BLTN, a novel metric, called Demand Overlap Coefficient (DOC), is presented in this paper. The DOC can be calculated for individual buildings or a district and describes which proportion of heating and cooling demands can be balanced inside buildings and between buildings. The DOC is calculated with time series for heating and cooling demands, taking special account of their simultaneity. For a real-world use case in Germany, it is shown that 25% of heating and cooling demands can be balanced in buildings and 45% can be balanced by the BLTN between buildings. The DOC is evaluated for 63 demand scenarios. Correlations show that for districts with a DOC larger than 0.45, BLTNs have lower annualized costs than a state-of-the-art heating and cooling system. BLTNs have higher exergy efficiencies for districts with DOCs larger than 0.3. With the derived correlations, the DOC serves as a practical metric in the planning process of BLTNs in order to identify and assemble building clusters with complementary demand profiles. [ABSTRACT FROM AUTHOR]

• The energy consumption of 38 Chinese district heating systems was investigated and compared. • Method to break down the consumption and evaluate the operational problems was presented. • Field measurements were conducted to evaluate problems leading to high energy consumption. • Overheating was responsible for 23% of total heat consumption. • Resistance, operation flow, and pump efficiency were three major problems in distribution networks. Worldwide, China has the largest district heating (DH) area and is also the fastest growing country. This paper presents field measurement results for operational energy consumption from 38 DHSs to fill in the gaps in understanding of the current operational issues of the district heating system (DHS). The average heat consumption during the heating period was 98.6 kWh/m2 and the monthly average electricity consumption for circulating pumps in the primary and secondary networks was 0.27 kWh/(m2 × month) and 0.29 kWh/(m2 × month), respectively. Thereafter, a systematic method for breaking down the energy consumption and quantitatively evaluating the underlying problems is presented. Based on several detailed measurements conducted in typical heat-exchange substations (HESs), it was found that overheating was the most prominent problem in energy-efficient buildings, constituting 23% of the total heat consumption. Another problem encountered was heat loss through pipes, which constituted approximately 5%–10% of the total heat consumption and was highly dependent on the actual conditions. In distribution networks, problems such as high resistance, high operational flow, and low pump efficiency were also identified and analyzed. Finally, practical energy-efficiency suggestions and future potential targets for the Chinese DHS are discussed from both a design and operational perspective. [ABSTRACT FROM AUTHOR]

District heating technologies are essential key elements of future sustainable energy systems. In order to support the design process, further information concerning long-term developments related to urban heat demand are crucial. Since building refurbishments are indispensable for achieving European CO2 reduction objectives, strategies for district retrofit orders are mandatory, which, in consequence, highly affect future energy demand of urban areas. In this paper, a data-driven approach for predicting long-term urban heating loads with Nonlinear Autoregressive Exogenous Recurrent Neural Networks (NARX RNN) based on an economically optimized retrofit order and two conventional retrofit orders is proposed. For demonstration, measured heat power data of a non-residential district in Germany is used for model training and statistical feature scenario generation enables mapping of future heat demand developments. [ABSTRACT FROM AUTHOR]