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Cleaner end-uses of energy, including electrified heating, represent a cornerstone of a decarbonised energy transition. On the other hand, many governments have adopted measures to mitigate energy poverty and facilitate access to modern energy services, including heating. Both objectives may be interrelated, since energy poor people are less likely to use cleaner (and costlier) heating fuels. This paper analyses the impact of energy poverty on the decision to use different heating sources and identifies whether the events of COVID and the Ukraine war have affected this decision. Thus, a multinomial probit model is estimated using information from a large database of Spanish households in 2019, 2021 and 2022. The results show that being energy poor increases the probability to use carbon-intensive energy sources for heating compared to electricity, and that COVID and the war in Ukraine have affected this relationship. The increase in energy poverty over those years has negatively affected the decarbonisation goal with respect to heating choices. The influence of those events on the probability to use electric heating depends on some household and dwelling features. Therefore, mitigating energy poverty increases the welfare of energy poor people while supporting the choice of cleaner heating. [ABSTRACT FROM AUTHOR]

Efficient cooling of the trans-critical CO 2 vapor compression cycle to improve system performance is a crucial research topic. This paper proposes an innovative approach called distribution compression (DC) to achieve the same effect as subcooling in a trans-critical CO 2 thermodynamic cycle. In the DC system, the trans-critical CO 2 at the gas cooler outlet is no longer further cooled but subjected to a secondary pressure boost and releases heat in ordinary heat sink conditions as in the gas cooler. Thermodynamics calculated the change in performance of the DC system under different working conditions with different secondary boost ratios. The optimal secondary boost ratio related to evaporation and gas cooler outlet temperatures under optimal discharge pressure based on the baseline system was obtained. The results show that compared with the baseline system, the DC system can effectively improve the system performance, and the maximum refrigeration COP increase is between 8.2 % ∼ 10.76 %, and the maximum heating COP increase is between 5.37 % ∼ 6.34 %. The cooling or heating capacity increase can reach up to about 26 %. The ideal secondary boost ratio in a DC system is not highly demanding, and the increased input power for the second input power for the secondary boost will not exceed 20 % relative to the baseline system. Comparing the COP of the DC system over current systems that only use a single subcooling technology still shows advantages. The DC system provides a new idea to improve the performance of the trans-critical CO 2 vapor compression cycle. [ABSTRACT FROM AUTHOR]

[Display omitted] • Localized heating systems are a proper solution for providing thermal comfort. • Providing personalized heating by radiation or conduction is more convenient, so the inhaled air is kept cool and pleasant. • Local radiant heating systems directly heat the body without heating the environment, leading to lower energy consumption. • With local radiant heating systems, proper thermal comfort and sensation can be achieved even at low air temperatures. Localized heating systems are a proper solution for providing thermal comfort while lowering energy consumption in cold environments. Local radiant heating systems provide thermal comfort at lower air temperatures than convective systems which heats air, resulting in cool and pleasant inhalation air. This paper reviews experimental studies regarding local radiant heating systems considering thermal sensation and comfort. These systems can heat body directly, often with a big view factor toward the body. They do not necessarily heat the air and environment, leading to lower energy consumption. Other types of heating systems combined with local radiant heating systems are also reviewed in this paper. According to reviewed studies, localized methods improved thermal comfort, and the same thermal sensation could be achieved in lower air temperatures, especially when using local radiant heating systems. To design local radiant heating systems properly, improvement of existing local thermal comfort and sensation modeling based on radiant heat transfer is needed. [ABSTRACT FROM AUTHOR]

• A model for calculating the thermal carrying capacity of water bodies was established. • The impact of meteorological parameters on water bodies was analysed. • Water source heat pumps failing to meet building heat demand in winter is analysed. • Solar radiation is the main source of thermal regeneration of water bodies. • Increasing the water depth or area can raise the thermal heat load-carrying capacity. Meteorological parameter changes not only affect the heat load-carrying capacity of the surface water, but also affect the heat load demand of the building, thus changing the heat load matching between the water source heat pump system and the users. In order to study the climatic adaptation of the heat load-carrying capacity, this paper establishes an analytical model of the water body's heat load-carrying capacity and the building's heat load with the solar radiation intensity, the change of the water body and the heat extraction time as variables. Experimental and simulation studies on the heat load-carrying capacity of lake water were carried out under the winter climate conditions in hot summer and cold winter areas. The results show that increasing the depth or area of the lake can improve the heat load-carrying capacity. Solar radiation is an important factor affecting the temperature of surface water body, the stronger the solar radiation the greater the temperature rise of the water body. Changes in outdoor air temperature have a significant impact on water temperature, and a sudden drop in outdoor air temperature will result in a sharp drop in water temperature. When the water body area was 3000 m2 and 50000 m2, the maximum integrated temperature drop of the water body was 15.0℃ and 9.7℃, which was 2.02 and 4.85 times of the temperature drop of heat extraction, respectively. Reduced heat load-carrying capacity of the surface water body or decreased COP of the heat pump is an important reason why the surface water source heat pump heat supply fails to meet the user's heat demand in winter. [ABSTRACT FROM AUTHOR]

• Load shifting experiments were performed in a single-family inhabited house. • Room radiators were controlled with variable set-point schedules. • Heat consumption was successfully shifted from the controlled rooms. • The total load shifting on a building level was limited. • A list of challenges for developing E-MPC in real buildings was identified. Recent simulation-based studies have indicated that load shifting using Economic Model Predictive Control (E-MPC) of radiators for residential space heating can be utilized for demand response purposes in energy systems. However, there is a lack of studies on whether this load shift potential can be realized in real, inhabited buildings. This paper reports on a field experiment aiming at realizing load shifting of space heating in a single-family house with a hydronic radiator system connected to the local district heating. Radiators in a limited number of 'active' rooms were controlled using set-point schedules mimicking the typical behavior of E-MPC. The results indicate that it was possible to load shift heating consumption in the 'active' rooms but that the load shift for the building as a whole was limited due to the hydronics of the radiator system. The paper also reports on the several practical issues encountered during the experiments – issues that in different ways are barriers to the practical realization of demand response from E-MPC of hydronic space heating systems. [ABSTRACT FROM AUTHOR]

This paper presents a two-stage framework for monitoring the decline of pipeline insulation and diagnosing leakage fault. The task of the first stage is to estimate the parameters of the pipeline network, so as to monitor the abnormal heat conduction data of pipelines, and use the estimation results to update the parameters of the pipeline model. The task of the second stage is to obtain the location and the water loss of after a leakage fault. In the framework, the tasks of the two stages are formulated into the problem of minimizing the divergence between the real system and the simulation system. And the problem is solved by the group search optimizer (GSO) algorithm with improved boundary search strategy in this paper. In the simulation tests, the framework is verified to be able to diagnose the faults. And in comparison with other heuristic algorithms, the GSO algorithm has the best ability to accurately diagnose the fault. Finally, the framework is applied in the cooling system, which shows that the framework has good migration capability. [ABSTRACT FROM AUTHOR]

A 5th generation district heating (5GDH) system consists of a low-temperature network used as a heat source for de-centralized heat pumps to serve heating demand. Until now, there is a lack of studies looking into the economic aspect of implementing the 5GDH concept. The performance characteristics, system dynamics, and economic feasibility of the 5GDH system are insufficiently investigated in cold climates. This paper aims to bridge the research gap by performing the techno-economic analysis of a 5GDH system using a case study based in Tallinn, Estonia. A detailed thermo-hydraulic simulation model is constructed in TRNSYS and Fluidit Heat. In addition, the uncertainty and sensitivities on the economic performance are analysed using Monte Carlo method implemented in Python. The study further analyses the effectiveness of using solar power technologies in reducing the cost of heating. For designed boundary conditions, the system can deliver heat at levelised cost of heating (LCOH) of 80 €/MWh. Integration of photovoltaic up to a limited capacity results in 1 % reduction when compared to the base case LCOH. The economic benefit of photovoltaic thermal is lower compared to photovoltaic. This study can provide a benchmark for the application of 5GDH systems in heating dominated regions. [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]

• A 5th-generation district heating and cooling system in business district is studied. • Design and operation strategies are based on load analysis and load forecasting. • Load predictions are based on machine learning algorithms and historical loads. • Larger flow rate in water loop than that on source-side makes system more efficient. • Source-network-load-storage collaboration in a district energy system is explored. The fifth-generation heating and cooling system (5GDHC) is a bidirectional low temperature network, which is a good solution for decarbonization and energy-saving in building cooling and heating. Because of its complex configurations, 5GDHC requires specific advanced control strategies for different scenarios. This paper aims to investigate 5GDHC with multiple sources in the business district in hot-summer and cold-winter zone through modelica simulation. The analysis and forecasting of district loads were used to study the design and operation strategies of 5GDHC. A suitable heat pump performance curve was presented for 5GDHC after comparing several heat pumps. And the larger the total flow in the network, the more beneficial it is for users. In this study, 5GDHC for the business district performed best when it adopted the strategy of continuous operation of the ground heat exchanger, nighttime operation of the surface-water coil, and supplemental cooling of the cooling tower upon it is needed, resulting in a 16.6% reduction in CO 2 emissions compared to the strategy that all sources operated continuously. Besides, carbon emission analysis showed the importance of balancing operational cost with carbon emission. This study will help optimize the design and operation of 5GDHC in business district scenarios. [ABSTRACT FROM AUTHOR]

The thermal process of heating buildings is characterized by the multivariable, nonlinear, and large time lag. Accurately predicting building heat loads is crucial for regulating building heating systems. However, the current black-box method of heat load prediction has challenges such as extensive data usage and weak integration with the building's heat transfer process. To address these challenges, a physics-guided long short-term memory (LSTM) model for dynamic heat load prediction in the next seven days based on data-driven and mechanism analysis was proposed. The data for the model were collected from in-situ measurement and numerical simulation. Specifically, the thermal mechanism was introduced to the training loss function of LSTM and the selection of input variables. The influence of the adaptive data time step on prediction accuracy was investigated. The main conclusions obtained from the current data in this paper are drawn as follows. 1) Refining solar radiation intensity calculation for each orientation reduced mean absolute percentage error (MAPE) of heat load prediction results by 0.02%–1.8% compared to horizontal solar radiation intensity. 2) Improving the training loss function decreased MAPE of heat load prediction results by 0.04%–0.43% compared with the original loss function. 3) Adaptive data time step lowered the MAPE of heat load prediction results by 0.08%–1.8% compared with fixed time step. 4) Mean absolute errors corresponding to those three aspects decreased by 25 kJ–558 kJ, 6 kJ–157 kJ, and 41 kJ–1881 kJ. In the future, wider promotion and application of the prediction model will lead to better performance and be more beneficial to energy saving and carbon reduction of the heating system. [ABSTRACT FROM AUTHOR]

• Long term field evaluation of forecast control of heating. • Easy integration with existing installations in buildings. • Widely applicable measure for energy savings around 10%. • Payback time below one heating season. The priority for reaching carbon neutral buildings by 2050 is to first increase energy efficiency in existing buildings by use of easily and widely applicable measures that are verified based on long-term field research. One such solution is a forecast control of heating systems, which can be quickly and easily integrated to existing weather based controls. However, there are still no long-term field evaluation and detailed analyses of the main features of such a system, which would provide a clear picture about the system's energetical and economical features and thus increase their wide application in existing buildings. This paper provides the data from a long term field evaluation of an innovative forecast control of heating systems (forHEAT), which can be easily installed (in less than 2 h) and integrated with existing installations in millions of existing buildings in Europe and throughout the world. The energy consumption for heating was evaluated in seven residential buildings and three public office buildings before and after the installation and use of the forecast control. The resulting energy savings averaged 13.4% in the residential and 10.7% in the public buildings located in continental European climate, with very cold winters. The payback time averaged a 0.6 heating season and in most case studies does not exceed a single heating season. [ABSTRACT FROM AUTHOR]

[Display omitted] • This paper summaries the present regulations and policies concerning M−TES (Mobilized thermal energy storage) in China. • The policies are analyzed based on the aspects including facility manufacture and operation, road transportation, and financial guidance. • The results can provide references for the government or policy makers to promote the development and safe operation of M−TES in China. Mobilized thermal energy storage (M−TES) is a promising technology to transport heat without the limitation of pipelines, therefore suitable for collecting distributed renewable or recovered resources. In particular, the M−TES can be flexibly used for the emergency heating in the COVID-19 era. Though the M−TES has been commercializing in China, there is not any specific regulation or standard for M−TES systems. Therefore, this paper summarizes and discusses the existing regulations and policies concerning M−TES in the aspects of facility manufacture and operation, road transportation, and financial support and guidance. Furthermore, the suggestions were presented including necessary consensus on the development of M−TES among different departments, consideration of local conditions when drafting or revising regulations and policies, sufficient investment, or subsidy on the R&D of M−TES, and qualification recognition of M−TES companies and staffs. [ABSTRACT FROM AUTHOR]

• Experiment in three homes using mixed-methods and physical measurements. • Indoor air temperature fluctuations like those of EMPC of space heating. • Night setback-users found the heating control unacceptable. • Acceptance was motivated by economic or environmental benefits. Recent simulation-based studies have indicated that Economic Model Predictive Control (EMPC) of space heating systems can exploit the thermal mass in residential buildings for demand response (DR) purposes in district heating systems. However, there is a lack of studies on residents' perception and acceptance of the fluctuating indoor air temperature behaviour inherent in EMPC of space heating. This paper reports on a case study featuring the residents of three one-story houses located in Denmark. The houses were equipped with technology enabling remote actuation of radiator thermostats and collection of various indoor environmental data. Four different temperature boost interventions mimicking the typical behaviour of EMPC of radiators were executed while a mixed-methods triangulation design, employing questionnaires and semi-structured interviews, was used to collect subjective data. Data showed that residents accepted the behaviour but only after the benefits of the EMPC were explained. The acceptance was motivated by either the prospect of saving money, environmental benefits, or a combination of both. The results thereby indicate that explaining the benefits of EMPC is important if residents are to abandon their current preferences and practices in favour of an EMPC concept. The explanation should consider the diversity in current preferences, expectations, and level of technological pre-knowledge. In addition, the paper also reports on a range of findings related to technical aspects of realising EMPC in practice. [ABSTRACT FROM AUTHOR]

[Display omitted] • A whole system approach to studying a low-temperature HGSHP system. • 3D coupled TH model with realistic boundaries and dynamic heat pump COP. • Design of a HGSHP system to support a 5th generation DHC network. • Different factors on performance of the HGSHP system and ground thermal behaviour. • Ground moisture transfer, cooling process and buried depth are important. Exploitation of shallow ground and its low-grade heat potential is fundamental to designing 5th generation district heating and cooling (DHC) networks. Horizontal ground-source heat pump (HGSHP) systems are a common way to utilize shallow geothermal energy. Realistic estimation and prediction of performance of a HGSHP system and shallow ground thermal behaviour should consider the whole system including building heating and cooling load, heat pump and ground heat exchanger, and the ground. This should be accompanied by realistic atmospheric and ground conditions. In this paper, a three-dimensional coupled thermal–hydraulic model with realistic boundary conditions adopting a whole system approach is presented. Dynamic heat pump coefficient of performance (COP) that depends on seasonal variation of heating/cooling demand and ground conditions are also considered. Model validations are conducted against experimental and analytical results in literatures. The model is applied for evaluating a HGSHP system to support development of a 5th generation DHC network on a potential site in the UK. Several influencing factors, such as ground moisture transfer, building thermal load mode, buried depth of ground loops, and initial ground temperature profile are studied to assess performance efficiency of the HGSHP system and evolution of ground thermal behaviour in response to heat extraction or rejection into the ground. The results show that 5% of the monthly total heat demand of the site could be met by the designed HGSHP system, consisting of 200 U-shaped ground loops buried at the depth of 3 m and pure water as the heat carrier. Overlooking the ground moisture transfer or hyperbolizing the ground saturation would overestimate the load-carrying capacity of the HGSHP system. The HGSHP system is more efficient with a higher heat pump COP under the heating and cooling mode than under the heating-only mode. Predicted performance of the HGSHP system improves with buried depth of the ground loops. The results also show that a 1 ℃ increase in the undisturbed ground temperature could suffice up to 8% of the monthly total heat demand of the site. [ABSTRACT FROM AUTHOR]

The development of the combined radiant floor and fan coil heating (RF-FCH) systems have improved the energy efficiency. In this study, the heating capacity and system operation state of the combined heating system were analyzed by experiments. The heating influencing factors of the combined heating system were investigated by two-way analysis of variance (ANOVA) and the Pearson correlation coefficient. Based on the technique for order preference by similarity to ideal solution (TOPSIS) the optimal operation scheme was determined. The results show that during the operation of the combined heating system, the fan coil bears significant heating capacity. The fan coil heating capacity accounts for about 62.2%-70.4% of the total heating capacity. The radiant floor plays an increasingly important role in the combined heating system with the decreasing outdoor temperature. The radiant floor response time varies from 1.5 h to 5.4 h. The fan coil responds faster to outdoor temperature changes compared to the radiant floor. The control of the fan coil can be considered as the dominant factor for dealing with outdoor temperature changes. The operation status of the RF-FCH system is mainly affected by the outdoor temperature. The energy conversion efficiency of the RF-FCH system increases with the increase of outdoor temperature. The energy efficiency ratio (EER) of the RF-FCH system varies from 2.2 to 3.2. The Pearson correlation coefficient analysis results are consistent with two-way ANOVA. Compared with the radiant floor, the indoor temperature and system energy consumption were more influenced by fan coil supply water temperature. When the evaluation indexes of the TOPSIS method have the same weight, the scheme with the fan coil supply water temperature of 32 °C exhibits a better performance. The innovation of this paper is that the best water supply scheme of the combined system is determined by TOPSIS method, which provides guidance for engineering projects. [ABSTRACT FROM AUTHOR]

Assessment methods to assess smart ventilation, in most countries focus only on comfort as criteria for the indoor air quality (IAQ) (Guyot et al., 2019). This is an issue as in doing so, pollutants that are known to cause harm to the human health are not taken into consideration while the exposure to VOCs will be elevated if the smart ventilation system lowers the ventilation flowrates to save energy (De Jonge & Laverge, 2021). This research addresses the question of what the impact of changing family sizes would be on the individual exposure to unhealthy pollutants for a smart ventilation system that only uses comfort related parameters to control the ventilation system. By introducing sources of Volatile Organic Compounds (VOCs) into a Modelica building energy and IAQ model of a typical Belgian apartment the occupant-dependent (CO 2 and RH) smart ventilation can be assessed for non-occupant dependent pollutants (VOCs). For three given smart ventilation systems, ten different households, with varying sizes and occupants are simulated. The results show that the presence of other family members influences the exposure to VOCs of an individual. One of the three smart ventilation systems is analyzed in detail, for this system, the minimum DALY count is 14.75 yr and maximum is 17.72 yr. They also show that the energy use of the building can be quite different although the only changing parameter in the simulation are the occupants. For the different simulated households, the minimum yearly energy use is 731kwh and maximum yearly energy use is 1319kwh. Similar results are obtained for the other two cases. Overall, the three smart ventilation systems show significant energy savings compared to the continuous nominal reference system but the expected impact on health increases. When designing a simulation-based assessment framework for residential ventilation, the occupant's behavior will always be an unknown factor to consider. The results indicate that in developing a simulations-based assessment framework, it is recommended to not assume just one household as in doing so, the system performance is not properly checked with regards to health and energy use during the lifetime of the system and the related expected variation in household types and sizes. The results in this paper confirm that a stochastic approach for assessing residential smart ventilation systems based on health-related pollutants (VOCs) should be investigated further. [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]

Ground source heat pumps (GSHP) are one of the most efficient systems that offer a promising reduction in greenhouse gas emissions and energy use in buildings; however, the electrification of buildings' heating and cooling using GSHP is facing two critical challenges: its high initial cost and potential adverse impact on the electrical grid. In this paper, to address these challenges, two novel systems are proposed in which a battery, a water thermal storage tank, and a phase change material (PCM) thermal storage tank are integrated, in different configurations, with a conventional GSHP system. In these systems, the grid electricity during off-peak periods is stored as heat or electricity in the thermal or battery energy storage systems. The stored energy is then used in peak building load conditions to reduce the peak power demand on the grid. New numerical models are developed to quantify the proposed systems' benefits. Furthermore, these newly proposed systems are compared with the conventional systems used in Quebec, Canada, and three previously proposed worldwide systems. Simulations are conducted for different commonly used design practices, including undersized and adequately sized heat pump capacities. The results show that the proposed systems can reduce the peak power demand and total energy requirement of a conventional system by up to 65.4% (9.28 kW) and 67.0% (19,722 kWh), respectively. Furthermore, the proposed systems' borehole length decreases by up to 21.8% (39 m) compared to the conventional GSHP system. [ABSTRACT FROM AUTHOR]

This paper investigates experimentally the cooling performance of a concept, where the radiant ceiling is suspended from the hollow-core concrete slab and by ventilation supply in the plenum and the perforations of the ceiling tiles, ventilation air is distributed without ducts and air terminals to the occupied zone. Literature has proven that this concept allows for more streamlined installation procedures and excellent performance in terms of thermal comfort and draught. The paper reports experimental results from a climate chamber, where the concept was tested under both steady-state and quasi-steady conditions. The steady-state conditions were chosen to map the cooling performance with different air change rates, and different ventilation and water supply temperatures. The results showed that for air change rates of 3 h−1 in the occupied zone and water supply temperature of 17 °C, the cooling output from the ceiling increased by 10 %. The concept was also tested under quasi-steady conditions in a 48 h cycle to quantify the thermal buffering effect of the exposed upper concrete slab when subjected to ventilation supply air. The effect amounted to 11–12 % increased cooling capacity at the end of the working day when the driving temperatures between air, water and thermal zones were at their maximum. [ABSTRACT FROM AUTHOR]

• This paper proposes a heating load decomposition method. • An IASHP prototype is produced based on the heating load decomposition method. • The advantages of the heating load decomposition method are demonstrated. • Maximize the heating performance of IASHP unit applied in severe cold region. • Heating performance of IASHP unit assisted with electric heating system is discussed. Although the inverter air-source heat pump (IASHP) and composite systems have a characteristic of energy conversion, the design of IASHP and the application of IASHP assisted with additional heat sources are absent based on the relationship between the demand side and supply side. Therefore, this paper proposes a heating load decomposition method to design IASHP with an auxiliary heat source system to offer users heating in severe cold regions. Specifically, the heating load decomposition method divides the heating load of the civil building into three regions by seeking heating energy balance points. It can get an optimal heating energy balance point with the best HSPF and an optimal design heating energy balance point with the best evaluating parameter. On these grounds, we produce an IASHP prototype. The experimental results confirm the superiority of the heating load decomposition method. Compared to the traditional design method, it improves by 6.5%-12.6% of heating capacity and 2.3%-17.4% of COP of IASHP porotype. Besides, the heating performance of IASHP assisted with an electric heating system selected by an optimal heating energy balance point is better than that of an independent IASHP heating system. In contrast, electric heating only pays 6.7% of the heating capacity of the IASHP unit operated at −27.0 °C of ambient temperature. [ABSTRACT FROM AUTHOR]

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p -value < 0.05, VIF < 5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data. [ABSTRACT FROM AUTHOR]

• Novel methodology for calculating cost-optimized refurbishment roadmaps is presented. • Coupling of building model for refurbishment and system model for heating technologies. • Refurbishment roadmap include timing and refurbishment measures for specific buildings. • Applying the optimization achieves cost savings of 6–16 % and CO 2 savings of 6–59 % • Heat pumps play a central role in the context of CO 2 reduction. A novel methodology for calculating optimized refurbishment roadmaps is developed in this paper. The aim of the roadmaps is to determine when and how should which component of the building envelope and heat generation system be refurbished to achieve the lowest net present value. The integrated optimization approach couples a particle swarm optimization algorithm with a dynamic building simulation of the building envelope and the heat supply system. Due to a free selection of implementation times and refurbishment depth, the optimization method achieves the lowest net present value and high CO 2 reduction and is therefore an important contribution to achieve climate neutrality in the building stock. The method is exemplarily applied to a multi-family house built in 1970. In comparison to a standard refurbishment roadmap, cost savings of 6–16 % and CO 2 savings of 6–59 % are possible. The sensitivity of the refurbishment roadmap measures is analyzed on the basis of a parametric analysis. Robust optimization results are obtained with a mean refurbishment level of approx. 50 kWh/m2/a of the building envelope. The preferred heat generation system is a bivalent brine-heat pump system with a share of 70 % of the heat load being covered by the electric heat pump. [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]

[Display omitted] • Dynamic evaluation of economic and energy benefits due to thermostatic valve installation. • Dynamic evaluation of economic and energy benefits due to heat metering installation. • The adoption of both thermostatic valves and heat metering least to a payback period lower than 2 years. • Analysis carried out considering several shapes of typical building. The aim of this paper is to propose a novel approach in order to accurately calculate the energy and economic savings due to the use of heat metering and thermostatic valves in residential buildings. The paper aims at proving that the present simplified approaches used in European Legislation may lead to significantly underestimate the profitability of this technology. The study is developed for four different typologies of buildings located in the city of Naples (South of Italy), including their geometrical and thermophysical properties. The buildings are first modelled in Google Sketchup and subsequently linked to the TRNSYS environment, which also includes a detailed model of the piping systems. The models allow one to evaluate, for every period of the year, energy demand, energy supplied by radiators, heat gains, transmission, etc. The developed models are used to calculate energy demands for three scenarios for each type of building: centralized heating systems not equipped with heat metering; thermostatic valves without heat metering; heat metering and thermostatic valves. The possible savings related to thermostatic valves and heat metering are estimated using the developed model. The results are compared with the ones provided by the Italian Standards. Results show that the thermostatic valves adoption leads to a significant reduction, up to 50%, of the thermal energy demand of the residential buildings and that all the proposed systems exhibit a remarkable economic profitability, with a payback period lower than 1.7 years. [ABSTRACT FROM AUTHOR]

The paper presents the results of heat demand forecasting during the off-season (summertime and transitional period) in a real district heating system. The hourly heat demand in the analyzed system ranges from 16 to 28 MW, depending on the month and hour of the day. Short-term prediction of the heat demand in the day-ahead horizon is needed for effective operation of production units in the Cogeneration Heat and Power Plant (CHP). The method of an hourly heat load predictions using a data-driven model is presented. The algorithm is based on the Generalized Additive Model with hour of the day, day of the week and day of the year as predictors. A way of increasing the accuracy of forecasts using the autoregressive model for residuals of the model was discussed. The influence of the training dataset size on the model error was also examined. The several versions of the model were evaluated by comparing forecasted results with real values during the district heating system's operation from June to the end of August. For the most accurate one, Root Mean Square and Mean Average Percentage Error were 0.84 MW and 3.3 %, respectively. [ABSTRACT FROM AUTHOR]

• Over the technologies' typical 20-year lifetime, most UK dwellings have a cost optimum low-carbon heating system using air source heat pumps. • Dwelling properties and spatiotemporal variabilities significantly change the optimum low-carbon technology from blue hydrogen boilers, direct electrical heating, and air source heat pumps, to ground source heat pumps. • Direct electrical heating is economically preferred over heat pumps in lower demand dwellings and with analysis over shorter timescales. • Incentives for low-carbon heating need to target adoption of efficient technologies to reduce the greater increase in network demands. An understanding of heating technologies from the consumers' perspective is critical to ensure low-carbon technologies are adopted for reducing their current associated emissions. Existing studies from the consumers' perspective do not compare and optimise the full range and combinations of potential heating systems. There is also little consideration of how spatiotemporal and dwelling variations combined alter the economic and environmental effectiveness of technologies. The novelty of this paper is the creation and use of a new comprehensive framework to capture the range of heating technologies and their viability for any specific dwelling's traits and climate from customers' perspective which is missing from current studies. The model optimises combinations of prime heaters, energy sources, ancillary solar technologies and sizes, thermal energy storage sizes and tariffs with hourly heating simulation across a year and compares their operation, capital, and lifetime costs alongside emissions to realise the true preferential heating systems for customers, which could be used by various stakeholders. Using the UK as a case study, the results show electrified heating is generally the optimum lifetime cost solution, mainly from air source heat pumps coupled with photovoltaics. However, direct electrical heating becomes more economically viable as dwelling demands reduce from smaller dwellings or warmer climates, as shorter durations of the ownership are considered, or with capital cost constraints from lower income households. Understanding this is of high importance, as without correctly targeted incentives, a larger uptake of direct electrical heating may occur, which will burden the electrical network and generation to a greater extent than more efficient heat pumps. [ABSTRACT FROM AUTHOR]

The capability to dynamically plan, predict, and control indoor conditioning allows to adapt to individual preferences of inhabitants and enables demand side management. While former mainly improves thermal comfort of inhabitants so does latter unlock ecological and financial opportunities mostly for energy utilities. Commonly, dynamic indoor conditioning is based on piece-wise constant indoor temperature constraints. This paper's contribution is the presentation of additional constraints: in particular ones expressed relative to the nominal behavior of a hydronic heating system. This allows to simultaneously harness the relevant process variables in particular during the pre-loading and post-loading phases of a load reduction. The findings are based on data sets acquired on 10 inhabited, residential buildings in Stockholm over a whole year. One of the findings is that building models need to be adaptable if predictive control is applied in practice. This adaptability is assured by a novel concept, i.e. a so called model manager on which the control is relying for the selection of the most accurate model. Centralized optimal control of buildings connected to a district heating network is challenging in practice due to a high computational load. In order to reduce it, the herein presented method elaborates plans only every hour instead of at every control step for optimal control. Since these plans cannot be optimal due to the lack of regular update a hitherto unknown cascaded control logic has been developed that corrects planning errors and other disturbances. Capabilities are demonstrated and compared to conventional controllers in dynamic simulations of a multi-zoned building. The herein presented method is to our knowledge the first to provide all flexibility desired by energy utilities and inhabitants alike through harnessing the consequences of transitions. [ABSTRACT FROM AUTHOR]

• Simplified models for heat transfer and surface temperature were established. • Calculated heat transfer and surface temperature agreed well with experimental data. • Heat transfer and surface temperature linearly changed with mean water temperature. • The pipe space clearly affected the heat transfer and surface temperature. • Heat transfer and surface temperature varied greatly as the transition changed. Prefabricated radiant heating and cooling (RHC) system is a typical form of high efficiency and lightweight radiant terminal, which has been extensively used in the residential and non-residential buildings. Heat transfer and surface temperature are the key parameters for rational design of a prefabricated RHC system. Therefore, in this paper, based on the analysis of the heat transfer mechanism, simplified models and numerical models were established for calculating the heat transfer and surface temperature of the prefabricated floor or ceiling RHC system. Compared with experimental test results, when the supply water temperature increased from 35 °C to 50 °C under heating condition or from 13 °C to 19 °C under cooling condition, the relative errors calculated by the simplified models were between −10.8% and 3.7% and between −3.8% and 5.0% for the heat transfer and surface temperature of the prefabricated floor RHC system, and ranged from 0.8% to 6.9% and from −0.7% to 0.3% for the prefabricated ceiling RHC system. Moreover, the calculated heat transfer and surface temperature of the prefabricated ceiling or floor RHC system using the simplified models were highly consistent with the numerical simulation results. Hence, the calculation accuracy of the proposed simplified models for the heat transfer and surface temperature can meet the requirements of engineering application, which will provide the support for the rational design of a prefabricated floor or ceiling RHC system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Simulation of residential building energy supply with heat pump or hydrogen systems. • 2050: Hydrogen economically-viable if H 2 -/Elec.-price is less than 34–61 % per kWh. • For conservative price predictions: Electric heat pumps are most economical solution. • Energy carrier switch for single-family houses: H 2 -/Elec.-price below 44 % per kWh. • Energy carrier switch for multi-family houses: H 2 -/Elec.-price below 58 % per kWh. • Fuel cells are emerging as an economically-viable option for multi-family houses. Fossil-fueled heating in the building sector is responsible for 16 % of Germany's total CO 2 emissions. Options for the climate-neutral heating of buildings include renewable electricity or renewable hydrogen. In this paper, we conduct a bottom-up study to investigate the role of hydrogen in the climate-neutral energy supply of ten selected residential buildings in comparison to electricity-based systems. Based on a demand simulation and linear optimization of the supply system, sensitivity analyses identify the threshold values of the hydrogen price for the use of hydrogen technologies (hydrogen boilers or fuel cells) in building energy systems and make the quantities of hydrogen consumed visible. The results specify the first installations of hydrogen-operated fuel cells in multi-family houses if the hydrogen price reaches 0.17 €/kWh H2 in 2050 at an electricity price of 0.31 €/kWh el. Generally, for different building types and electricity supply prices, it indicates that the use of hydrogen becomes economically-viable if the price of hydrogen supply is in the range of 34–61 % of the price of the electricity supply per kWh and below. For the case of green hydrogen obtained using renewable electricity, it is highly questionable whether hydrogen supply will be that much cheaper than direct electricity supply, making its economical use in buildings uncertain. [ABSTRACT FROM AUTHOR]

The central and local policies have played an important role in the implementation of rural clean heating, and have also accelerated the improvement of air quality in Northern China. Among these policies, the subsidy policies have the most significant impact on rural clean heating. However, due to some inappropriate subsidy policies, they have also caused many problems, such as the reburning of scattered coal. To effectively solve the current problems and further optimize the subsidy policies, the Beijing-Tianjin-Hebei region is selected as the research object in the present paper to evaluate the subsidy policies of rural clean heating, and analyze the insufficiency of central policies as well as the burden of subsidy on local finance. The results show that there is an issue of inequality on the central subsidy policies of rural clean heating, and a huge difference in the central government's subsidy amount per household more than 8 times between different cities. In terms of the local subsidy policies, the ratio of clean heating subsidy to local fiscal expenditure fluctuate more and more from the province, city to county level, and some counties have been at a high fiscal pressure level. Based on the current situation of rural clean heating in the Beijing-Tianjin-Hebei region, it is suggested to optimize the subsidy policies systematically from the optimization of work goals, the adjustment of central policies, the improvement of local policies and the enhancement of policy assessment. This study is aimed to provide references for the policy optimization of rural clean heating in Northern China. [ABSTRACT FROM AUTHOR]

Due to the inherent complexity of multi-dimensional solutions for transient conduction in a multilayered building element, most heat balance-based algorithms assume that conduction occurs only in one dimension—through the building element between the inside and outside environments. Usually, since the length and width of the elements are much greater than the thickness of the element, this is a valid assumption. However, there are some cases such as hydronic radiant slabs where this assumption may not lead to an accurate estimate of the energy consumption of the system. In a hydronic radiant slab, water tubes are embedded in a slab, and hot or chilled water is circulated to meet any heating or cooling loads. The energy consumption of such a system will depend highly on the temperature of the water being sent to the slab (i.e., produced by the boiler or chiller). The temperature of the water that must be sent to the slab will depend on the spacing of the tubes, the multilayer construction of the building element, and the boundary conditions to which the construction is exposed. Thus, to accurately predict the energy consumption of such a system, a transient two-dimensional heat conduction model must be integrated with a heat balance-based simulation. This paper demonstrates the potential loss of accuracy associated with the one-dimensional radiant system models by providing a comparison of one- and two-dimensional solutions using EnergyPlus. [ABSTRACT FROM AUTHOR]

• Heat exchange performance optimization study of the coaxial deep borehole heat exchanger. • Optimal insulation backfill depth for deeply buried pipes. • Multi-factor orthogonal simulation experiment. • Multiple linear regression analysis for optimal insulation backfill depth. Coaxial deep borehole heat exchanger (DBHE) coupled with ground source heat pump (GSHP) system has been widely applied in building heating. Insulation backfill is essential for the heat transfer performance of DBHE in colder regions. However, few studies focus on the combined influence of multi-factors on the optimal insulation backfill depth. In this paper, an orthogonal experiment was designed to explore the influence of multi-factors on the optimal insulation backfill depth of DBHE by using a numerical heat transfer model. Sensitivity analysis concluded that heat transfer factors such as inlet flow rate (A), inner pipe thermal conductivity (B), inlet temperature (C), geothermal gradient (D), and pipe depth (E) all affected insulation backfill depth of DBHE, and the comparison order of significance are C > D > B > A > E. An optimal insulation backfill depth exists for different DBHE heat transfer conditions. Compared with no insulation backfill, the average heat extraction of buried pipe under optimal insulation backfill conditions increased by 6.09 kW, with an average growth rate of 8.78 %. In addition, multiple linear regression analysis was utilized to examine the relationship between affecting factors and the optimal insulation backfill depth, based on the findings of orthogonal tests. The outcomes revealed that inlet temperature, inner pipe thermal conductivity, and pipe depth were positively correlated, with the highest standardized positive correlation value of 0.755 for inlet temperature. In contrast, inlet flow and geothermal gradient were negatively correlated, with the highest standardized negative correlation coefficient of −0.420 for the geothermal gradient. The linear regression equation could predict the magnitude of optimal insulation backfill depth with diverse input parameters. The relative error between the predicted and simulated values of the equation was less than 5 %. The findings of this research can guide the popularization and application of the GSHP coupled with the DBHE system in colder regions. [ABSTRACT FROM AUTHOR]

• A new methodology to investigate the impact of thermal mass is defined. • The use of unrepresentative boundary conditions could lead to inaccurate conclusions. • High thermal mass helps to decrease and regulate the internal temperature. • High thermal mass could increase energy use in the summer and winter seasons. • Isolating thermal mass through internal insulation results in better energy performance than external insulation. Contradictory conclusions have been reported on whether thermal mass reduces or increases energy demand in hot and cold climates. A novel approach to measuring the impact of thermal mass on the building's energy consumption is presented. The method aims to better represent reality and applies two different control conditions simultaneously in a numerical model: the first condition, which has been used in past studies, adjusts the internal boundary condition based on the time duration of heating/cooling activation (simulating an occupancy pattern) and the second, which has not been used in past studies, adjusts the internal boundary condition based on both the time duration and the internal temperature (simulating an occupancy pattern and the thermostatic control system). When investigating the impact of thermal mass on the internal temperature in a scenario where no heat is transferred into the building, the high thermal mass outperforms the low thermal mass, showing a time-shifting effect, long time lag, and small decrement factor. However, when modelled using the method presented in this paper, high thermal mass results in greater energy consumption during summer and winter periods in Saudi Arabia. During transition seasons where temperature swings occur on either side of the indoor set-point temperatures, thermal mass reduces thermal transmission. The impact of thermal mass is also investigated for several climatic conditions in Saudi Arabia. Simulation results show that an internally exposed thermal massive wall section results in greater energy consumption when compared to a similar building with isolated thermal mass (i.e. insulated internally). This is due to the fact that even though the internal temperature inside the building is being cooled/warmed up to the set-point, the thermal mass continues to transfer heat that is absorbed by the building's fabric from/to the interior, placing a greater demand on the cooling/heating system. Over the course of a year, however, the impact of thermal mass is negligible when compared to other factors, such as the insulative properties of the building's fabric. [ABSTRACT FROM AUTHOR]

• Nonlinear hybrid MPC for buildings energy systems based on Modelica. • Time-variant linearization of the nonlinear Modelica optimization problem. • Automated creation of the linearized optimization problem in every MPC iteration. • Integration of on/ off control, discrete operation states and operation modes. This paper presents a nonlinear hybrid Model Predictive Control (MPC) approach for building energy systems based on Modelica. The MPC approach takes into account two characteristics that are very common for building energy systems: nonlinearities (inherent in the building envelope and Heating, Ventilation and Air Conditioning (HVAC) systems) and discontinuities (in the form of on/ off operation, discrete operation states and operation modes). The hybrid MPC approach integrates both continuous and discrete optimization variables into the control concept and thus is capable of controlling building energy systems with binary or integer decision variables, switching dynamics or logic if-then-else constraints. By employing a time-variant linearization approach, nonlinear Modelica optimization problems are approximated with high accuracy and transformed into a linearized state-space representation. Based on the linearization output, a linearized optimization problem is generated automatically in every MPC iteration, which is extensible by various integer characteristics and is accessible for a wide range of mixed-integer solvers. A simulation study on a nonlinear Modelica building energy system demonstrates the control quality of the proposed toolchain revealing a small linearization error and successful integration of multiple integer characteristics. The benefits of the approach are manifested by comparing its performance with different reference control strategies. [ABSTRACT FROM AUTHOR]

In practice, monthly temperature records play a major role calculating the heating and cooling degree-days of the air conditioner management in buildings. Classically, heating and cooling degree calculations are based on the comparison of outdoor temperature measurements with a standard level called the base temperature. Truncating the temperature series at a constant base temperature causes heating (deficits) and cooling (surpluses) degrees. Since outdoor temperature records are of random character, future predictions with probabilistic and statistical methods are convenient means for calculations. All previous methodologies in the literature are based on crisp logic with simple mathematical calculations. This paper proposes a new methodological approach by converting the actual temperature record probability distribution function (PDF) into a probabilistic standardized degree indicator (SDI) in normal (Gaussian) PDF form with zero mean and unit standard deviation. Furthermore, as a new evaluation methodology fuzzy logic inference calculations are provided. SDI is divided into seven classes, three for cooling, heating, and a single class for uncooled-unheated states. Heating and cooling degree changes according to SDI values are presented with crisp and fuzzy sets. The application of the methodology is made for Kadıköy urban area on the Asian side of Istanbul, Turkey. In the case of fuzzy set SDI air conditioned operation, it has been determined that there is cooling energy saving of approximately 25% compared to the crisp set. The same is true for the heating degree-day side. [ABSTRACT FROM AUTHOR]

[Display omitted] • A hierarchical approach for automatic layout of an underfloor heating system is proposed. • The routing problem is formulated as a shortest path problem in a proper routing graph. • An order relation is defined to separate the intersecting paths. • A depth-first layout algorithm based on recursion is developed to solve the coverage path planning problem. The layout of an underfloor heating system determines its heating performance. Conventionally, the design is completed by qualified experts using professional software, but this method is inefficient and heavily relies on the experts' previous experience. This paper proposes a hierarchical approach for the automatic design of underfloor heating systems aimed at residential buildings, and the underfloor heating layout problem is decomposed into a routing problem and coverage path planning problem. First, the routing problem is formulated as a shortest path problem in an appropriate routing graph and solved to provide the routing of pipes for further coverage. Subsequently, a depth-first layout algorithm is developed to recursively simplify the coverage path planning problem to obtain the basic rectangle layout, achieving uniform coverage of the given layout zone. Simulation results on two houses show that, unlike one popular commercial platform, the proposed approach generated feasible solutions in all 13 test instances. The new method improved the minimum temperature, average temperature, average percentage of nodes greater than 30 °C, and total energy efficiency by 3.18 °C, 0.79 °C, 3.23%, and 4.19%, respectively, with a lower variance on average. These improvements lead to a higher coverage rate, more even thermal distribution, and stronger robustness under flexible parameter selection. [ABSTRACT FROM AUTHOR]

[Display omitted] • In the US, carbon savings are readily achievable by transitioning to heat pump technologies for the vast majority of homes. • The heat pump performance required to achieve carbon and cost neutrality varies by a factor of four across the US. • Energy cost neutrality is much harder to achieve than carbon neutrality. • Achieving carbon and energy costs savings is much easier when replacing older, low efficiency equipment. In order to meet climate goals, it will be necessary to significantly reduce the greenhouse gases emitted by homes. A key factor in the US is to reduce the on-site combustion of fossil fuels for heating end-uses and to replace this with use of electric heat pump technologies connected to a low-carbon grid. The replacement of natural gas furnaces with electric heat pumps is a key home decarbonization strategy. However, the potential for space heating electrification to reduce greenhouse gas emissions depends on the carbon dioxide equivalent (CO 2 e) content of the electricity used by the heat pump. This varies considerably depending on the source of electricity, with large state to state variability. Furthermore, household energy costs are likely to be impacted by the electrification of space heating, because retail energy prices for both natural gas and electricity in each state vary by factors of seven and four, respectively. Contractors, energy programs, government and building code officials, as well as consumers need clear indications of the likely CO 2 e and energy cost impacts of proposed electrification projects, because these will affect decarbonization choices and rationales around scaled heating electrification. Government and utility programs also need to be aware of the likely outcomes of any supported/incentivized measures. In this paper, we investigate these effects by looking at new metrics to analyze the change in CO 2 e emitted and the cost to meet home heating loads when switching from a natural gas furnace to a heat pump for the contiguous 48 states of the mainland US. [ABSTRACT FROM AUTHOR]

• Occupants on-demand heating control behavior in a rural residential building is investigated. • Independently controlled split-type heating equipment were used to elucidate actual demand patterns. • Data collection over three years under an interference avoidance scheme. • Five representative intermittent heating patterns were obtained from a real-world case study. A better understanding of actual heating demands is crucial for optimizing operational heating systems, because disparities between expected load and actual demand are key factors in inefficient heating system design, implementation, and corresponding energy loss. Additionally, the discrete, energy consumption-based billing systems applied to freestanding rural residential buildings encourages reductions in energy waste but produces spatially and temporally distinct heating patterns. Conventional heating systems have only basic controls and slow response times that cannot reflect actual user demand. Hence, this paper presents an experimental scheme for measuring room-wise heating demands, and thus, the actual heating demand patterns of rural residential buildings. A case study was conducted on a typical rural residential building in Beijing to validate the method's feasibility. Real-world usage patterns were obtained using indoor environment sensors and independently-controlled heating devices that collected the operational parameters of each room over three years, in a long-term non-intervention study design. Clustering analysis and various indicators were used to characterize heating demand for each room: heating patterns, usage intensity, and temporal variation. In most case, the occupants heated only a few rooms, rather than the whole building. These results have potential real-word implications for predicting occupant heating behavior and energy conservation. [ABSTRACT FROM AUTHOR]

[Display omitted] The rapid development of urbanization has created high demand for central heating systems. This trend has led to an increase in energy consumption for central heating, which has made China's energy-saving transformation extremely difficult. However, the channel by which urbanization impacts and the future trends of energy consumption for central heating are still unclear. Therefore, this study employs the Logarithmic Mean Divisia Index (LMDI) method to decompose the effect of urbanization on changes in energy consumption for central heating during 2001–2019 in China. We investigate the contribution of urbanization from demographic, economic and spatial perspectives. Additionally, a scenario analysis is used to explore trends in energy consumption for central heating in different projected urbanization scenarios. The results show that urbanization has a positive impact on energy consumption for central heating, particularly in underdeveloped regions. Demographic urbanization has the strongest positive effect on energy consumption for central heating, followed by spatial urbanization and then economic urbanization. Compared with the expansion of area and economic development, population agglomeration will bring more energy consumption for central heating. The forecasting results indicate that energy consumption for central heating will reach 176–189 Mtce in 2030, which is approximately 1.4 times the current level. This work quantifies the energy consumption for central heating in the future under urbanization. The policy recommendations given at the end of the paper will provide a reference for the formulation of energy consumption for central heating. [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]

[Display omitted] • Heating system is the most crucial parameter for renovation. • Deep renovation is neither cost-effective nor climate-friendly considering future uncertainties. • Heating system replacement alone has lower overall emissions than solely envelope renovation. Buildings are responsible for a large share of CO 2 emissions in the world. Building renovation is crucial to decrease the environmental impact and meet the United Nations climate action goals. However, due to buildings' long service lives, there are many uncertainties that might cause a deviation in the results of a predicted retrofit outcome. In this paper, we determine climate-friendly and cost-effective renovation scenarios for two typical buildings with low and high energy performance in Switzerland using a methodology of robust optmization. First, we create an integrated model for life cycle assessment (LCA) and life cycle cost analysis (LCCA). Second, we define possible renovation measures and possible levels of renovation. Third, we identify and describe the uncertain parameters related to the production, replacement and dismantling of building elements as well as the operational energy use in LCCA and LCA. Afterwards, we carry out a robust multi-objective optimization to identify optimal renovation solutions. The results show that the replacement of the heating system in the building retrofit process is crucial to decrease the environmental impact. They also show that for a building with already good energy performance, the investments are not paid off by the operational savings. The optimal solution for the building with low energy performance includes the building envelope renovation in combination with the heating system replacement. For both buildings, the optimal robust cost-effective and climate-friendly solution is different from the deep renovation practice promoted to decrease the energy consumption of a building. [ABSTRACT FROM AUTHOR]

• The cascaded PCMs charge–discharge processes and cycle entransy models are studied. • To run stably and efficiently, the charge–discharge cycle model is recommended. • The thermal performance of cascaded PCMs may be worse than that of single PCM. • The cascaded PCMs is suitable for scenes with large temperature differences. • In heating systems, the total NTU of cascaded PCMs is recommended between 4.5 and 6. Thermodynamic analysis can guide the application of the cascaded latent heat storage system (CLHSS) for space heating. However, in previous studies, the CLHSS charge–discharge process and the cycle are not distinguished, and the applicability of the corresponding models is not analyzed. In addition, the technical advantages of CLHSS in heat utilization are still unclear. This paper solved the above three problems to provide theoretical guidance of the CLHSS integrated into heating systems. First, the CLHSS charge–discharge cycle is the special charge–discharge processes in which the initial and final states of each PCM are consistent. The CLHSS charge–discharge processes and cycle models are established and optimized. Second, the optimization results of charge–discharge processes model cannot ensure the same initial and final states of each PCM, which leads to unstable operation and performance degradation of the CLHSS. Thus, the CLHSS charge–discharge cycle model is recommended. Third, when the total number of heat transfer unit (NTU) of CLHSS is less than that of single-stage latent heat storage system (SLHSS), the thermal performance of CLHSS may be worse than that of SLHSS. Besides, the use of CLHSS instead of SLHSS is suitable for scenes with large temperature differences between heating equipment and heating terminals. Finally, parameters effects on optimization results are analyzed. From the perspective of improving entransy efficiency, it is recommended that the total NTU of CLHSS during charge process and discharge process are between 4.5 and 6, and as close as possible. [ABSTRACT FROM AUTHOR]

• Sleeping thermal comfort using a bed-based ASHP was numerically studied. • A digital thermal manikin (DTM) was used to simulate a sleeping person. • The PTS - WPD model was used to evaluate sleeping thermal comfort. • Four factors affecting sleeping thermal comfort were numerically analyzed. Sleeping is an important human activity and heating system is needed for a comfort sleeping thermal environment in winter. By combining the merits from both an air source heat pump (ASHP) and a Chinese-Kang heating system, a prototype bed-based ASHP (B-ASHP) system has been proposed, and several design/operating parameters were experimentally and numerically studied previously. A numerical study using a digital thermal manikin (DTM) on the impacts of four influencing factors, i.e., operating mode, bed surface temperature (t bed), thermal resistance of mattress (R mat), and thermal resistance of quilt (R q) on sleeping thermal comfort was carried out, and the study results are reported in this paper. The numerical study results suggested that firstly, to maintain a suitable sleeping thermal environment, the use of only the Horizontal section (H-Section) of the bed-based heating terminal of the B-ASHP system was adequate; however using the Horizontal and Vertical section (H + V-Section) could minimize the temperature difference between the micro-climate close to the bed and outside environment, although with a higher energy consumption. Secondly, t bed of the bed-based terminal should be carefully selected, and a t bed of 44 °C could both meet the requirement of thermal comfort and acceptable operating efficiency of the B-ASHP system. Thirdly, the use of a mattress would reduce the heat transfer from the bed-based terminal to a sleeping person and indoor space, however an excessively higher R mat of mattress would reduce the heating capacity and operating efficiency, leading to a cold sleeping environment. Finally, the use of a quilt would help prevent the heat loss from a sleeping person, thereby maintaining a warmer sleeping thermal environment, however a higher-than-necessary R q of quilt would decrease the sleeping thermal comfort. [ABSTRACT FROM AUTHOR]

• The comprehensive survey on individual household heating in Serbia. • Results reveal barriers and opportunities for the successful energy transition. • The obsolescence of HSs, low efficiency, and lack of funds are evident. • Noticeable potential for achieving energy and GHG savings. • Subsidies and raising environmental awareness are recognized as policy measures. This paper presents the results of the household survey on individual household heating systems in Serbia. The survey was conducted in the period October to December 2020 with the participation of 1100 households with individual household heating systems. The information collected in the questionnaire can be separated into three main parts: basic household data, current heating system characteristics, and households' perceptions and attitudes. The survey results provide unique and comprehensive information concerning individual household heating systems and the main barriers and drivers for a successful energy transition in the future. The results show the obsolescence of household heating systems, low efficiency, insufficient investment in thermal insulation in the past, and lack of financial resources for investing in sustainable heating. On the other hand, this survey highlights the positive attitude of about half of households towards potential subsidizing of the cost of new heating systems. This survey presents a valid starting point for defining instruments aimed to improve energy efficiency in the household sector, diminish its influence on climate change, and secure energy transition towards sustainable heating systems. The obtained results should be indicative for middle-income developing countries at the beginning of the energy transition process. [ABSTRACT FROM AUTHOR]

• A comprehensive overview of various modeling methods for BTES is presented. • Validated against the TRNSYS DST model and real-life monitoring data. • Three operation strategies of BTES in DH system are investigated. • Six building insulation and weather scenarios to increase the results' robustness. • The time-scheduled combined control strategy is more beneficial among all scenarios. This paper presents a modeling and simulation method that supports energy performance assessment and operation strategy investigation of borehole thermal energy storage in the Chifeng district heating (DH) system. A living laboratory in Chifeng, China that integrates a 0.5 million m3 borehole thermal energy storage system, an on-site solar thermal plant and excess heat from a copper plant is presented. The research adopts Modelica models from open source libraries to evaluate the system. The validity of the borehole thermal energy storage model is evaluated through an inter-model comparison study and an empirical validation test. We used the validated model to investigate three operation strategies. We conclude that the time-scheduled combined operation strategy is more beneficial for the studied system regarding CO 2 emission reduction. [ABSTRACT FROM AUTHOR]

In the current economic situation in Ukraine, the operation of heat supply systems occurs at a reduced temperature of circuit water. The increased temperature graph of 95/70 °C due to the high cost of fuel is impractical. The experience of such countries as Denmark, Germany, Finland, Sweden and Holland with developed centralized heat supply indicates the need for the first-class equipment of an individual heating point (IHP) of a building with an automatic control system, and then the transition to technology with a reduced temperature graph is carried out. Therefore, the modernization of heat supply systems in Ukraine aimed at the use of a reduced temperature graph will require a transition to closed independent heating systems, to qualitative and quantitative regulation and to automation of consumer IHP systems. A lot of district heating systems in Poland also require modernization to meet the requirements of the European Directive EED 2018/2002. This paper presents the results of numerical study of the influence of design and operating parameters of the heat supply network on the choice of the optimal temperature and flow- rate of circuit water of a distric heating system (DHS). [ABSTRACT FROM AUTHOR]

• Novel energy conservation measure yields up to 12% of energy savings. • Grey-box data-driven model efficiently models monozone building. • Building energy consumption optimized while satisfying thermal comfort constraints. • Energy consumption of a commercial building is optimized during winter and summer. This paper proposes a novel energy conservation measure that optimizes the planning of heating and cooling systems for tertiary sector buildings. It consists of a model-based predictive control approach that employs a grey-box model built from the building and weather data that predicts the building heat load and indoor temperature. Different from classical optimization approaches where the discretized differential algebraic equations are integrated into the optimization formulation, our model is calibrated using black-box multiobjective optimization, which allows for decoupling the predictive model from the optimization problem, thus having more flexibility and reducing the total computational time. Moreover, rather than requiring the angle of solar radiation, solar orientation and solar masks to calculate the radiation data, our approach requires only a simple model of the solar irradiance. The calibrated model is then used by heating and cooling optimization strategies that aim at reducing the energy consumption of the building in the next day while satisfying the indoor thermal constraints. The proposed approach was applied in a case study of a commercial building during heating and cooling seasons and the results show that it was able to yield up to 12% of energy savings while having a mean power forecast error of 8%. [ABSTRACT FROM AUTHOR]