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Heat recovery in industry is limited by thermodynamic and economic factors. Increased heat recovery in an existing heat exchanger calls for higher costs in terms of capital and pumping due to increased exchanger size and pressure drop. One design option to offset the rapid growth of surface area to meet the upgraded heat load is to seek strategies to increase the heat recovery by increasing the heat transfer coefficient with a moderate increase on pressure drop. Compabloc heat exchangers have the construction features that make them suitable for such purposes. This paper presents a new design methodology for this type of exchanger and discusses its application in retrofit projects. The approach exploits the use of utility paths as the simplest and more practical way of identifying energy savings projects. The importance of analysing and quantifying temperature disturbance propagations is discussed. Applications to two case studies demonstrate the economic viability of using compabloc exchangers to achieve large energy recovery and savings. It is demonstrated that with an additional pumping cost of $66,776.12 USD/year, a total surface area of 1140.8 m2 and capital investment of $1062,272.0 USD, 24.8 MW of additional energy can be recovered, saving $5339,675.52 USD/year, giving a payback of 2.8 months. • A practical approach to the use of compabloc heat exchangers in retrofit applications is introduced. • Compabloc exchangers are sized using a new design methodology and new generalised thermohydraulic correlations. • Utility paths and temperature disturbance propagation are important aspects of the approach. • Compabloc exchanger can achieve high heat recovery, energy savings and short payback periods. [ABSTRACT FROM AUTHOR]

The construction sector accounts for 40% of total energy consumption and is increasing. To reduce energy consumption of heating and cooling systems during peak demand while maintaining thermal comfort, phase change materials (PCMs) are used more and more. Appropriate application of PCM and design of latent heat thermal energy storage (LHTES) requires in practice an in-depth knowledge of the thermal properties of PCMs. The aim of the paper is to present the results of experimental determination of the properties of two commercially available, organic PCMs – RT22HC and RT28 HC, using T-history method and pipe Poensgen apparatus. Results of experimental tests showed that these low-temperature PCMs could effectivity store heat and cold in a narrow temperature range of approx. 7 K for RT22 HC and about 3–4 K for RT28 HC. The average measured latent heat values are 190 kJ/kg for RT22 HC and 244 kJ/kg for RT28 HC. The distribution of energy stored in RT22 HC shows the peak in the temperature range of 21–23 °C (with 20–50 kJ/kgK for heating, 22–71 kJ/kgK for cooling). For RT28 HC this range is 27–28 °C (75–130 kJ/kgK for heating, 40–125 kJ/kgK for cooling). The diagrams of enthalpy present small hysteresis (0.5–1 K) in these materials. Thermal conductivity measurements using pipe Poensgen apparatus demonstrated that these PCMs have a low conductivity of 0.12–0.33 W/mK. The presented experimental research is intended to provide the data necessary for the correct design of LHTES with RT22 HC or RT28 HC intended to use in heating and cooling systems and to maintain thermal comfort in buildings. • RT22 HC and RT28 HC were tested using T-history method and pipe Poensgen apparatus. • The average measured latent heat is 190 kJ/kg for RT22 HC, 244 kJ/kg for RT28 HC. • Results of T-history method and three-layer calorimeter are in good agreement. • Pipe Poensgen apparatus was used to determine thermal conductivity of PCMs. • Tested PCMs confirmed their potential to reduce peak energy consumption. [ABSTRACT FROM AUTHOR]

The heat pump operated single-stage humidification-dehumidification desalination system, configured with a subcooler and a heat regenerator, has been proven highly effective in improving both freshwater productivity and energy efficiency. To investigate the potential benefits of increasing the number of humidification stages, this paper presents a heat pump operated two-stage humidification-dehumidification desalination system by adding a pre-humidifier. Subcooler and condenser of the heat pump are used as the heat sources of the main humidifier and the pre-humidifier, respectively. Through parametric studies, a comparative analysis is conducted on the thermodynamic and economic performances of both the heat pump operated single-stage system and two-stage system at various operating conditions. The results show that such system modification can greatly improve system performances. Compared to the single-stage system, the maximum freshwater productivity of the two-stage system is 42.89 kg/h, increased by 19.77 %; the peak gain output ratio is 7.93, up by 9.53 %; and the lowest specific electricity consumption is 79.34 kWh/m3, reduced by 15.15 %. Furthermore, the freshwater production cost for the two-stage system, ranging from 7.78 to 13.33 $/m3, is also superior that of the single-stage system, further demonstrating its substantial value in practical product development and market promotion. • A heat pump operated two-stage humidification-dehumidification system is proposed. • Performances of single and two-stage systems are compared at identical conditions. • Freshwater production costs of the two-stage system range from 7.78 to 13.33 $/m3. • The two-stage system is significantly more efficient than the single-stage system. [ABSTRACT FROM AUTHOR]

Industrial steam heating is a significant aspect of energy consumption in China, playing a crucial role in industrial energy efficiency. Historically, demand response research has predominantly focused on the electricity sector, with limited emphasis on steam supply. This study explores a novel Time-of-Use pricing approach for steam heating systems, anchored in the demand response theory of price incentives. It develops a peak-valley segmentation method by considering both the load differences between supply and demand and the thermal storage capacity of the pipeline system. Additionally, the paper delves into user response characteristics to formulate an optimized Time-of-Use pricing model for steam heating systems. Implemented in a Jiangsu-based case study, the model demonstrates significant efficiency improvements: it reduces the peak-valley load difference by up to 68.3% and cuts steam purchasing costs by ¥135,000. Furthermore, the alignment between the users' total steam load curve and the heat source's steam supply is enhanced by 18.8%, illustrating the model's effectiveness in balancing demand and supply. • Cluster analysis to extract steam user load characteristics. • Divide peak/valley times based on network storage and user traits. • Create a multi-objective Time-of-Use model for steam pricing optimization. • Carry out a case validation in an actual industrial park in Jiangsu. [ABSTRACT FROM AUTHOR]

In this paper, TRNSYS is used to simulate the heating systems of air-cooling concentrating photovoltaic/thermal (CPVT) coupled air source heat pump and water-cooling CPVT coupled air source heat pump. Besides, Grasshopper is adopted for multi-objective optimization of air-cooling system. This study not only proposed two hybrid systems and enriched the research of CPVT coupled air source heat pump, but also proposed a multi-objective optimization method, which uses Grasshopper to invoke TRNSYS. Compared with the air source heat pump system, the annual average COP of heat pump in the air-cooling system increases by 22.8%, and that of the water-cooling system decreases by 6%. The primary energy saving rate of the air-cooling system is 1.06 times and 6.67 times that of the water-cooling system and the air source heat pump system. The optimized air-cooling system reduces the annual total cost by 2.83%, and increases the energy utilization coefficient by 4.76%. The proposed air-cooling system has obvious advantages in energy saving and improving COP of heat pump. This study is useful for the cost savings and energy conservation of air-cooling concentrating photovoltaic/thermal (CPVT) coupled air source heat pump systems based on urban public buildings. • Models of different CPVT coupled ASHP systems are established in TRNSYS. • The optimization method integrates the advantages of TRNSYS simulation and the advantages of GH parameterization. • The systems are analyzed and compared from energy utilization coefficient, exergy efficiency, primary energy saving rate, annual total cost and net present value. • The ACPVT-ASHP system performance is best when the ASHP capacity is 9.9 kW and the length of PV cells is 1.819 m. [ABSTRACT FROM AUTHOR]

The problem addressed in this work is the enhancement of energy efficiency in buildings, primarily focused on heating control. The paper highlights the importance of addressing this challenge, given that HVAC systems are responsible for over 60% of total energy consumption in buildings, making them the largest energy consumers in both the residential and nonresidential sectors. This paper presents a methodology for developing a model predictive control (MPC) system based on artificial neural network (ANN) models, with the aim of improving the energy efficiency of buildings. This approach involves the creation of a training dataset using dynamic thermal simulation tools, enabling the learning of the ANN model that is responsible for predicting future states within an MPC optimization loop. Additionally, the implementation leverages advanced technologies such as Field-Programmable Gate Arrays (FPGAs), specifically the PYNQ board, Wi-Fi modules, and MQTT communication to enhance scalability, deployment, and adaptability. The study evaluates the proposed Neural Network Model Predictive Control (NNMPC) strategy implemented on the PYNQ, reporting a substantial reduction of 38.53% in heating energy consumption in buildings compared to a basic On/Off control approach for 24-hour simulation. This outcome underscores the solutions significant potential for energy savings in building heating systems. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, energy conservation and carbon reduction in the heating industry have become the focus of attention. However, severe heat loss is currently occurring in the secondary heating system due to hydraulic imbalance, which is unable to supply heat according to users' needs. In view of this, a thermodynamic-hydraulic model of users' demand for heat and flow rate for the heating system is established. Then, a novel method to regulate hydraulic imbalance is proposed, with the dynamic heat demand satisfied by regulating the valve opening based on NSGA-II. The optimization results show that the comprehensive hydraulic imbalance coefficient has been reduced from 23.08 to less than 0.019, which means that almost 100% of users can get heat supplies corresponding to their needs, while the energy consumption is reduced by about 30%. Additionally, when there are 1000 population and iteration steps, good convergence and high speed are presented using this method. In summary, an on-demand optimized model of hydraulic balance for the secondary heating network is put forward, which provides powerful engineering support and guidance for intelligent heating construction. • This paper presents a method to regulate the hydraulic balance of network using NSGA-II according to the heat demand. • This paper combines the demand flow regulation of users with the resistance analysis of the heating network. • The hydraulic balance can be implemented greatly by using the hydraulic imbalance coefficient as the optimization goal. • The number of iteration steps in the algorithm has an effect on the optimization results. [ABSTRACT FROM AUTHOR]

Reducing building energy consumption and increasing the use of renewable energy are essential to energy conservation. Photovoltaic thermoelectric heat pumps have been considered as a sustainable measure to supply detached houses with hot water, especially those that even do not have access to the power grid. This paper investigates a stand-alone photovoltaic/thermal integrated thermoelectric water heating system (PV/T-TEWH). A dynamic model of PV/T-TEWH is developed and validated. The performance of the system in Lhasa, Beijing, Changsha and Guangzhou is simulated and analyzed respectively, and the economics of the system are compared. Results show that PV/T-TEWH can rely on the electric energy it generates without additional power supply when the current is less than or equal to 1.4 A in Lhasa and 1.0 A in Beijing, Changsha and Guangzhou. The annual total heat gain of the PV/T-TEWH system increases as the operating current increases, but the COP of the system falls with the rise of operating current. When the system is operating at the currents of 0.6 A, 1.0 A, 1.4 A, and 1.8 A, the payback period shortens with the increase of current. Lhasa has the shortest payback period among four cities and it is only 2.2 years when the working current is 1.8 A. The PV/T-TEWH system provides a new method for building hot water supply, especially for detached houses in remote areas. • This paper proposes and investigates a photovoltaic/thermal integrated thermoelectric water heating system (PV/T-TEWH). • A dynamic model suitable for simulating the PV/T-TEWH system is developed and validated. • The annual performance of the system in Lhasa, Beijing, Changsha and Guangzhou is simulated and analyzed. • The economics of the system in different cities are compared. [ABSTRACT FROM AUTHOR]

Adsorption carbon capture has shown its superiority in energy consumption and cost investment when compared with common amine scrubbing technologies. However, high regeneration energy demand of adsorbents is still a challenge for large-scale application. This paper proposes a temperature vacuum swing adsorption system integrated with auxiliary heating and cooling technology. Absorption chiller and double-stage absorption heat transformer (DAHT) are introduced from the perspective of adsorption and desorption process of CO 2 capture system. Results indicate that when the duration of each step increases from 25 min to 45 min, the CO 2 recovery rate decreases from almost 100 %–75.7 %, and CO 2 purity increases slightly from 89.6 % to 91.1 %. Considering the temperature grade of waste heat, heat consumption of the absorption chiller assisted system is lower than that of DAHT for original and adjusted cases at a generation temperature of 58 °C. If the desorption temperature decreases from 120 °C to 100 °C, heat consumption of the absorption chiller decreases from 1.90 GJ·ton−1 to 1.76 GJ·ton−1, but the average capture capacity decreases from 306.3 ton·ton−1 ad to 272.1 ton·ton−1 ad. It is demonstrated that both absorption chiller and absorption heat transformer could be promising solutions to reducing the energy consumption of CO 2 capture system. Absorption chiller has a priority over DAHT in regions with low temperature heat sources. Moreover, a tradeoff between adsorbent loss and heat consumption should be found when choosing the appropriate heat pump for practical application. [Display omitted] • Adsorption carbon capture integrated with absorption chiller is initially proposed. • Absorption chiller is beneficial for reduction of heat consumption of capture. • Decrease of desorption temperature has great influence on system performance. • Heat pump assisted adsorption capture is a promising way for energy saving. [ABSTRACT FROM AUTHOR]

50–80 °C heat sources are abundant in renewable energy areas and industrial processes. However, they are difficult to be effectively used due to their ultralow grade. In order to solve this problem, this paper presents a high-efficient hybrid adsorption refrigeration system combing with desiccant coated heat exchangers. In this study, the performance of the hybrid system is experimentally investigated and parametric effects are fully discussed. Results indicate that the hybrid system operates efficiently across a wide heat source range of 50–80 °C. A high-temperature hot water facilitates the cooling production of the hybrid system, while a low-temperature hot water is more beneficial to the COP promotion. Also, a lower cooling water temperature, higher air temperature, higher relative humidity and longer switch time can enhance system performance. The optimal cooling capacity is quantified as 4579 W when powered by 80 °C hot water and the COP reaches its maximum of 0.673 under a heat source temperature of 50 °C. Comparison results show that compared with present systems, the hybrid system has greater adaptability as well as higher efficiency in utilizing 50–80 °C ultralow-grade heat sources, and can satisfy the simultaneous demand for cooling and dehumidification, which offers a promising way to high-efficient energy utilization and sustainable development. • A hybrid adsorption system using desiccant coated heat exchangers is presented. • The hybrid system operates efficiently across a wide heat source range of 50–80 °C. • The cooling capacity and COP reach 4579 W and 0.673, respectively. • The hybrid system provides a promising solution for efficient energy utilization. [ABSTRACT FROM AUTHOR]

• A two-layer framework is proposed for building HVAC and associated multi-energy consumption optimization. • 100% renewable complementarities are proposed for building multi-energy supplies. • A R-C thermodynamic network is formulated to model the building HVAC. • AC slow charging and DC fast charging types of EVs are considered and managed via a novel real-time supply–demand pricing. Building heating, ventilation, and air conditioning (HVAC) and associated energy consumption make up the more and more important part of the world, whose reduction provides a cost-effective path to the "dual carbon" goal. This paper proposes a two-layer management of HVAC-based multi-energy buildings under proactive demand response of fast/slow-charging electric vehicles (EVs). In this paper, the building HVAC is mathematically formulated via a R-C thermodynamic model, which coordinates with multi-energy converters and storages to form a 100% renewable building. The building management is a challenging optimization problem due to its severe constraints and strong spatio-temporal couplings. In the first layer, a day-ahead multi-energy dispatch is formulated to economically optimize the electrical, heat, gas energy carriers. In the second layer, alternating current (AC) slow charging and direct current (DC) fast charging types of EVs are considered and managed via a novel real-time supply–demand pricing mechanism. After acquiring the economical dispatch references in the first layer, the second layer implements a model predictive control (MPC)-based real-time scheduling to handle the multi-energy supply–demand fluctuations. The original two-layer optimization is further handled via mixed-integer linear program (MILP) reformulation for high-efficient solving. Comparisons have shown the advantageous performances of the proposed two-layer optimization over economics and practicability. Simulations results show that the overall system operating cost can be reduced by at most 3.01% with a higher operational flexibility in building management. [ABSTRACT FROM AUTHOR]

Coal-fired heating, mainly used in North China, has caused serious environmental problems. Schemes to replace coal have been established, but they are not suitable for all scenarios. This paper proposes a heating scheme that uses a methanol heating stove (MHS) to meet the demand for clean, low-cost rural heating. The economy, emissions, and energy consumption of the MHS were analyzed. The scheme was compared with five common rural heating methods. The effects of the methanol price, power grid transformation, and gas pipeline construction on the annual cost of each heating scheme were investigated using a theoretical model. The MHS emitted 66 % less CO 2 and 95 % less SO 2 and NO x and consumed 54 % less standard coal than bulk coal heating stoves. The low electricity supply required to vaporize methanol contributed to the cost and emission reduction. Methanol price fluctuations warrant government subsidies to incentivize the implementation of the scheme. For increased adoption, we recommend that the MHS be used in areas with low population densities and methanol prices. This approach can therefore be an ideal substitute for "coal-to-electricity" and "coal-to-gas" methods in areas that lack access to power or gas supplies and can replace air-source heat pumps in severe cold zones. [ABSTRACT FROM AUTHOR]

Financial issues have been always one of major priorities in scheduling of energy systems. Although these systems are able to serve several types of energy demands but generated emission by these systems is a challenging problem. Since improvement of each one of mentioned issues has negative effects on the other issue therefore a trade-off solution is necessary to be obtained between these issues. In this paper, a multi-objective model has been presented to satisfy both economic and environmental objectives of a hub energy system in the presence of demand response program. In the proposed paper, ε-constraint and max–min fuzzy satisfying methods have been employed to solve and select the trade-off solution. The main reason of implementation of demand response program is to reduce operation cost and improve environmental performance of hub energy system. In fact, demand response program transfers some percentage of load from peak periods to off-peak periods to flatten load curve which leads to reduction of cost and emission. A mixed-integer linear programming has been used to simulate the proposed model and general algebraic modeling system software has been utilized to solve it. A sample hub energy system containing renewable and non-renewable energy resources has been studied and comparison results are presented to validate efficiency of proposed techniques. [ABSTRACT FROM AUTHOR]

In times of great transition of the European construction sector to energy efficient and nearly zero energy buildings (nZEB), a market observation containing qualitative and quantitative indications should help to fill out some of the current gaps concerning the EU 2020 carbon targets. Next to the economic challenges, there are equally important factors that hinder renovating the existing residential building stock and adding newly constructed high performance buildings. Under these circumstances this paper summarises the findings of a cross-comparative study of the societal and technical barriers of nZEB implementation in 7 Southern European countries. The study analyses the present situation and provides an overview on future prospects for nZEB in Southern Europe. The result presents an overview of challenges and provides recommendations based on available empirical evidence to further lower those barriers in the European construction sector. The paper finds that the most Southern European countries are poorly prepared for nZEB implementation and especially to the challenge/opportunity of retrofitting existing buildings. Creating a common approach to further develop nZEB targets, concepts and definitions in synergy with the climatic, societal and technical state of progress in Southern Europe is essential. The paper provides recommendations for actions to shift the identified gaps into opportunities for future development of climate adaptive high performance buildings. [ABSTRACT FROM AUTHOR]

• Machine Learning is used for energy use prediction of a solar-assisted heat pump. • Attention mechanism and time series decomposition is used to improve model accuracy. • Various combinations of input features are compared. • Results can provide valuable insights for developing Neural Network models. With improved insulation of building envelopes and the use of low-temperature space heating systems, the share of energy use for domestic hot water (DHW) production in buildings has increased significantly, and nearly become the most energy-expensive service in modern buildings. Early prediction of the energy use for DHW is required for many advanced applications such as smart control, demand-side management, and optimal operation of electric or heat storage. However, predicting energy use of the solar-assisted water heating system is more challenging than typical DHW systems, as it is strongly affected by two stochastic phenomena, demand pattern and solar radiation. Given the increasing use of solar-assisted water heating systems, this paper aims to evaluate the potential to predict energy use in such systems using a novel machine learning approach. In this novel model, a Long-Short Term Memory (LSTM) neural network is enhanced by (1) implementing the attention mechanism, a recent development in deep learning inspired by human vision to pay selective attention to the input data, and (2) decomposition of input data into sub-layers. The performance of simple LSTM neural network, Attention-based LSTM neural network (ALSTM) and Attention-based LSTM using decomposed data (ALSTM-D) are compared to a Feed-Forward neural network as a baseline model. Results show that LSTM, ALSTM and ALSTM-D models have a Mean Absolute Error (MAE) of 25%, 28% and 41% lower than Feed-Forward model, respectively. These results indicate the superior performance of the proposed ALSTM-D model over conventional models for solar-assisted DHW systems. [ABSTRACT FROM AUTHOR]

• Propose a CCHP system integrated natural gas reforming system with solar energy. • Design and construct models of the PAFC-CCHP hybrid system. • Present the energy and exergy analysis of the proposed system. • Discuss the effects of key parameters on thermodynamic performance. Hybrid natural gas combined cooling, heating, and power (CCHP) systems integrated with solar technologies offer the efficient use of distributed energy resources for reducing the use of fossil fuels and greenhouse gas emissions. This paper proposes a novel CCHP system, using the phosphoric acid fuel cell (PAFC) as the prime mover, integrated with the natural gas reforming with solar energy assistance. Their respective thermodynamic models are constructed for simulation of the system thermodynamic performance. The simulation results demonstrate that the energy efficiencies of the hybrid system with solar energy assistance are 55.12% for the heater mode and 66.77% for the chiller mode, while the exergy efficiencies are 32.87% and 31.59%, respectively. Similarly, when solar energy is not available, its energy efficiencies are 59.24% and 69.18%, while its exergy efficiencies are 40.09% and 39.01%, respectively. In the PAFC–CCHP hybrid system, the exergy efficiencies are key components in the overall efficiency, and the efficiencies with and without solar energy are 29.34% and 36.95%, respectively. Solar energy and exergy share is employed to analyze the solar energy contribution, and they are 36.1% and 35.6%, respectively. Meanwhile, the parametric analysis is also carried out to evaluate the effects of key parameters on the performance. The results show that increasing the reforming temperature, influenced by solar energy, improves the natural gas conversion and boosts the hydrogen concentration of the syngas fed into the PAFC, which increases the overall exergy efficiency. However, the effect of the reforming temperature is reduced when the reforming temperature is higher than 1073.15 K. [ABSTRACT FROM AUTHOR]

• Advanced climate-resilient energy retrofit technology reduces the use of non-renewable energy in the building sector. • Renewable District Heating as an optimal technology in deep energy renovation strategies. • Sustainable cities and buildings are feasible by Centralised District Heating system powered by biomass. • Key Performance Indicators (KPIs), to achieve nZEB performances established in the European legislations. This paper presents the implementation of a biomass-fuelled District Heating System (DHS), as a part of a deep energy renovation exercise to achieve a climate-resilient campus with minimum carbon dioxide emissions. The case study is carried out for the University of Valladolid, an average-sized university in Spain, with a continental weather climate. Prior to renovation, the different building blocks had a wide-ranging level of fossil fuel consumption for space heating and domestic hot water ranging between 60 and 430 kWh/m2·year. The application of this centralised heating system allows to achieve the minimum threshold for near zero-energy buildings (nZEB) of 100–120 kWh/m2, in accordance with the Spanish Standards. These values correspond to the maximum European indicators for offices in continental weather conditions. Results of this comprehensive study show that 15 out of the 19 buildings reached the nZEB target, due to the proposed strategy. The overall carbon dioxide emissions have dropped by 92.69% as compared to the original fossil-fuel powered boiler, thus bringing carbon dioxide emissions down to 1.57 kgCO 2 /m2·y. Therefore, it is shown that deep energy renovation strategies through renewable energy DHS have the potential of achieving nZEB for universities in continental weather conditions. [ABSTRACT FROM AUTHOR]

• A constraint equivalent model for heat networks is proposed. In this model, the operational constraints of heat networks are mapped to the feasible region of CHP units, which protects the privacy of heat networks. • A boundary point search method is further developed to efficiently solve the constraint equivalent model and construct a high-accuracy approximation of actual feasible region. • A cooperation method with the rolling horizon strategy is proposed considering the uncertainties of heat and power loads. In the proposed cooperation method, the feasible region of CHP units is provided to the power system only once, which alleviates the communication burden. • Compared with other cooperation methods, simulation results show the advantages of the proposed cooperation method in balancing privacy protection and the quality of the solution. • The impact of heat storage tanks and uncertainties of heat loads on the boundaries of the feasible region is further analyzed. The cooperation of combined heat and power (CHP) systems can improve efficiency in energy utilization by fully utilizing the complementarity between heat and power. However, heat and power systems are operated by different companies where data sharing is restricted for privacy reasons, thus posing significant obstacles to collaboration. This paper proposes a coordinated operation method for CHP systems based on the constraint equivalent model. To preserve the operational constraints of heat networks and protect data privacy, a boundary point search method is firstly developed, where the operational constraints of heat networks are mapped to the feasible region of CHP units. Then, a multi-period cooperation model considering uncertainties of both networks is established based on the proposed constraint equivalent model and the rolling horizon strategy. Moreover, the impact of heat storage tanks and uncertainties of heat loads on the boundaries of the feasible region for heat networks is further analyzed. Simulation results demonstrate the effectiveness of the proposed constraint equivalent model and the cooperation method. [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]

This paper proposes a compound parabolic concentrating (CPC) vaporized desalination system with preheating and heat recovery. In the preheating and CPC heating subsystems, the water and heat-conducting oil are respectively employed as the working medium. The seawater is heated by circulating water and heat-conducting oil in the heat exchangers, thereby preventing collector corrosion. The latent heat recovery of the steam improves the energy utilization rate, and the spraying of the feedwater onto the vaporized plate enhances the heat and mass transport and the vaporization efficiency. The influences of the feedwater temperature and ambient temperature on freshwater production under various levels of solar irradiance are illustrated by calculation. The system freshwater production, heat loss, heat efficiency, and heat recovery efficiency are experimentally explored. The preheating and heat recovery increase the average inlet temperature of the CPC heating subsystem to 60.6 °C, thereby an energy savings of 6720.68 kJ/d. The maximum hourly production and the daily freshwater production of the system is 4.55 kg/h and 15.72 kg, respectively. The average heat recovery utilization rate of the system is 0.39. • A novel desalination system with preheating and heat recovery. • More than 6720.68 kJ/day energy saving with preheating and heat recovery. • Enhanced heat and mass transport transfer by spraying. • Daily freshwater yields of 15.72 kg/day. • Preheating, heat recovery and spraying increase the freshwater yields by 25.2% and 61%, respectively. [ABSTRACT FROM AUTHOR]

This paper presents new metrics to measure the effect of thermal mass on the energy required to heat and cool buildings. Previous studies have been flawed as they have not considered the interaction between intermittent occupancy and thermal mass, which has a significant impact on overall energy use. However, existing parameters do not adequately capture these effects, so the new metrics developed in this paper are used to analyse the impact of thermal mass in hot climates with active cooling, and cold climates with active heating. The results agree with existing literature that high thermal mass structures are likely to be effective in hot climates; however, in cold climates the drawbacks of high thermal mass likely outweigh the advantages, and high thermal mass can cause an increase in energy use. This finding has implications for the design of buildings in cold climates, and contradicts the commonly-held assumption that high thermal mass is correlated with low energy use. The new metrics (transient energy ratio and effective U -value) provide a generalisable method to quantify these effects. They are further used here to analyse the dynamic performance of heavily insulated buildings and show that high thermal mass often leads to higher energy use in cold climates. [ABSTRACT FROM AUTHOR]

Abstract The goal of this paper is to evaluate the advantages achieved through the adoption of low impact energy saving strategies for an independent natural gas fired boiler heating system in a recently built residential building in Rome. For this purpose, an existing apartment was selected as a case study and dynamically simulated in TRNSYS with which the model was validated. Low impact retrofit solutions and heating system management were considered as possible solutions to achieve energy savings. The chosen retrofit solutions consist of envelope elements replacements and building automation controls improvement while heating system management depends on occupants' behavior. Overall, 36 scenarios were considered, starting from the combination of 3 comfort temperature set-points, 2 insulation levels for transparent components, 2 types of zone comfort set-point control with 3 dead-band temperatures. Each case is evaluated in terms of energy results and economic results. The simulation results provide energy savings up to 44% when windows are replaced lowering their transmittance nearby 32%. The choice of a proportional control for zone temperature set-point compared to a simple on-off control guarantee energy saving up to 39% when temperature set-point is low (19 °C) and controls dead-band is 0.5 °C. The effect of different temperature control dead-bands is higher when proportional controls are adopted (up to 40% passing from 2 to 0.5 °C dead-band for 19 °C set-point). Energy consumption reductions up to 63% are achieved if the indoor temperature set-point is lowered 2 °C, underlining the importance of occupants' behavior. At last, an analysis on socio-economic impacts was performed, based on the results of a previous study focused on the externality costs due to pollutants emissions. Highlights • Energy advantages achieved through the adoption of low impact energy saving strategies for an independent gas fired boiler were evaluated. • An existing apartment of a modern residential building in Rome was selected and dynamically simulated in TRNSYS. • 36 energy saving scenarios were considered. • Each case was evaluated in terms of energy and economic results. • An analysis on socio-economic impacts was performed, based on the externality costs due to pollutants emissions. [ABSTRACT FROM AUTHOR]

Abstract The coupling between heat pumps and renewable energy sources is a recognized strategy to reduce primary energy consumption at the household level. This paper contributes to the present-day discussion concerning solar-assisted heat pumps for heating/cooling and to produce domestic how water. In particular, this study presents the results of a field study concerning a novel solar-assisted dual-source multifunctional heat pump, installed in a detached house in Milan. The proposed system couples hybrid photovoltaic/thermal (PVT) panels with a multifunctional and reversible heat pump. The heat pump is equipped with " air-source " and " water-source " evaporators, connected in series and operated alternatively, based on the ambient conditions, system parameters and operating modes. In addition, the PVT panels are used, by employing two storage tanks, to produce domestic hot water and to provide a heat source to the " water-source " evaporator. The proposed system has been tested experimentally, showing interesting and promising results: the system has been able to maintain high efficiencies in the different seasons and has been able to use the solar energy to support the production of domestic hot water. It was found that the use of the " water-source " evaporator allowed to significantly increase the performance of the system and to avoid the defrost cycles. Highlights • We present a novel solar-assisted dual source multifunctional heat pump. • We summarize the results of a field trial. • We provide seasonal performances of unit installed in a detached house. • We provide daily performances of unit installed in a detached house. • We relate seasonal and daily performances. [ABSTRACT FROM AUTHOR]

Abstract A Trombe wall (T-Wall) is widely applied to buildings due to the advantage of saving fossil energy and improving indoor environment, etc. However, a traditional T-Wall usually has the drawbacks of low thermal efficiency and thermal inertia, which lead to poor heating performance and significant energy loss at night. To overcome the above drawbacks, in this paper, an improved T-Wall was designed and its heating performances were experimentally investigated. Firstly, a detailed description on the improved T-Wall, test-bench and measurement system were reported. Then, the experimental procedures, conditions and data reduction were given. Finally, the experimental results were analyzed and discussed. The results revealed that the air temperature in the test room was higher than 16.0 °C during more than half of the testing time, and the minimum air velocity was 0.35 m/s at the vent outlet, which could circulate the indoor air to improve the thermal environment. Furthermore, the daily thermal efficiency of the improved T-Wall was higher than 50% during the daytime. Therefore, the results of this study provided valuable insights for improving the heating performance of T-Wall. Highlights • A Trombe wall with novel configuration is proposed. • An experimental study of the novel designed Trombe wall is conducted. • The novel Trombe wall is able to heat the indoor space effectively and rapidly. • The daily thermal efficiency of the novel T-Wall is higher than 50% during the daytime. [ABSTRACT FROM AUTHOR]

Abstract Beyond the definition and measurement of energy poverty, which have mainly attracted research interest over the last decades, attention has recently begun to turn to a broader notion of energy vulnerability. So far, this has mostly been approached on a theoretical base, suggesting the incorporation of broader socio-economic aspects into the energy poverty framework. However, the quantitative measurement of energy vulnerability is still an unexplored field of research. In this paper, the "Vulnerability Index" is developed, which, based on stochastic analysis, quantifies the vulnerability of a population to the energy poverty ratio, compared to a reference population. Moreover, Sensitivity Analysis quantifies the particular contribution of various parameters to the problem, by determining their weighting factors. As case study, the vulnerability of Greek mountainous regions with respect to the country level was studied. The results showed that households living in mountainous regions are more vulnerable versus those of the whole country, at 89.7%. It was also found that energy policy should focus on raising incomes of mountainous population and, afterwards, on energy saving measures and reduction of heating cost in mountains. The methodology suggested can address social inequalities of vulnerable population groups, in terms of energy poverty. [ABSTRACT FROM AUTHOR]

Highlights • Increase of self-consumption of photovoltaic electricity for heating by factor six. • Simple control algorithm to use building mass as thermal battery with heat pump. • Operation cost of the heat pump can be cut in half. • Building overheating up to 26 deg C is equivalent to 2 m3 water heat capacity. • Electricity grid consumption 40% less with only 10% additional building heat loss. Abstract The purpose of this paper is to show the possible increase of self-consumption of photovoltaic (PV) electricity production for a building by intelligent use of thermal masses in the building. TRNSYS simulations were carried out for an electrically driven ground heat pump in combination with PV, thermally activated building systems and water storage (TES) in small single-family buildings. Several different control strategies adapting set-temperatures in combination with different building types and heat capacities were investigated. For a single-family house with 8900 kWh space heating and domestic hot water demand per year and a 20 m2 PV system, the solar fraction (SF) increased from 11% for a standard configuration up to 61% with maximized use of overheating of the TES (2000 L tank) and the building mass. The running cost for the heat pump due to grid electricity consumption (0.18 EUR per kWh) decreased from 420 EUR per year – in the reference case without PV – to 373 EUR (SF = 11%) with PV, but in the standard configuration without PV self-consumption optimization, and to 69 EUR per year (SF = 61%) with PV self-consumption optimization, if the remaining PV electricity was completely sold at 0.05 EUR per kWh. [ABSTRACT FROM AUTHOR]

Highlights • A component-based method of machine learning for performance prediction in engineering. • Components instead of one monolithic model extend reusability and generalization. • Flexible design support by machine learning for early design phases. • Internal parameters between components allow insights in the “black box” of machine learning. • Good prediction accuracies (error < 3.9%) for test cases different from the training model. Abstract Machine learning is increasingly being used to predict building performance. It replaces building performance simulation, and is used for data analytics. Major benefits include the simplification of prediction models and a dramatic reduction in computation times. However, the monolithic whole-building models suffer from a limited transfer of models and their data to other contexts. This imposes a vital limitation on the application of machine learning in building design. In this paper, we present a component-based approach that develops machine learning models not only for a parameterized whole building design, but for parameterized components of the design as well. Two decomposition levels, namely construction level components (wall, windows, floors, roof, etc.), and zone-level components, are examined. Results in test cases show that, depending on how far the cases deviate from the training case and its data, high prediction quality may be achieved with errors as low as 3.7% for cooling and 3.9% for heating. [ABSTRACT FROM AUTHOR]

Gas turbine combined cycle (GTCC) based combined cooling, heating and power (CCHP) or combined heating and power (CHP) system driven by natural gas is encouraged to set up for district heating/cooling demand in China due to the clean and efficient energy conversion. This paper presents a GTCC based CCHP system, which consists of a heavy-duty gas turbine, triple-pressure heat recovery steam generator (HRSG), steam turbines, heat exchanger and absorption chiller. Turbine inlet temperature (TIT) strategy and inlet guide vanes (IGV) strategy for the gas turbine are adopted to access the part load performance. The energy distribution and exergy destruction of the CCHP system are investigated under different gas turbine loads. The primary energy saving rate (PESR) and carbon dioxide emission rate (CDER) are set up to evaluate the system at various gas turbine loads and steam extraction ratios. The ability of shaving peak power for the system is investigated. The results show that IGV plays a role in increasing the steam turbine power output and reducing the exhaust heat in HRSG but causes more exergy destruction in the steam turbine expansion process. The PESR and CDER have been enhanced as the steam extraction ratio increases for the same gas turbine load. The IGV strategy reinforces the part-load performance of the CCHP system. For instances, the PESR has been enhanced from 0.2409 to 0.3108, and CDER has been strengthened from 0.8274 to 0.8465 by the IGV strategy at half of gas turbine load and without steam extraction. For the same heating load, both PESR and CDER are enhanced by the IGV strategy. The ability of supplying heating is deteriorating as the decrease in TIT. The ability of shaving peaking power is going to be deteriorated as heating load increases. For the small heating load, like 50 MW, the advantage of the IGV strategy is prominent, the PESR and CDER is advanced 5.81% and 1.48% respectively by the IGV strategy. [ABSTRACT FROM AUTHOR]

Housing Stock Energy Models (HSEMs) play a determinant role in the study of strategies to decarbonise the UK housing stock. Over the past three decades, a range of national HSEMs have been developed and deployed to estimate the energy demand of the 27 million dwellings that comprise the UK housing stock. However, despite ongoing improvements in the fidelity of both modelling strategies and calibration data, their longevity, usability and reliability have been compromised by a lack of modularity and openness in the underlying algorithms and calibration data sets. To address these shortfalls, a new open and modular platform for the dynamic simulation of national (in the first instance, the UK) housing stocks has been developed—the Energy Hub (EnHub) . This paper describes EnHub’s architecture, its underlying rationale, the datasets it employs, its current scope, examples of its application, and plans for its further development. In this we pay particular attention to the systematic identification of housing archetypes and their corresponding attributes to represent the stock. The scenarios we analyse in our initial applications of EnHub, based on these archetypes, focus on improvements to housing fabric, the efficiency of lights and appliances and of the related behavioural practices of their users. In this we consider a perfect uptake scenario and a conditional (partial) uptake scenario. Results from the disaggregation of energy use throughout the stock for the baseline case and for our scenarios indicate that improvements to solid wall and loft thermal performance are particularly effective, as are reductions in infiltration. Improvements in lights and appliances and reductions in the intensity of their use are largely counteracted by increases in heating demand. Housing archetypes that offer the greatest potential savings are apartments and detached dwellings, owing to their relatively high surface area to volume ratio; in particular for pre-1919 and inter-war epochs. [ABSTRACT FROM AUTHOR]

Despite the fact that district heating is viewed as a sustainable and promising solution for urban heating, its expansion in historic areas is fraught with challenges and barriers. This paper examines the heat supply of Old Tallinn's historic centre following the transition to district heating. The study identified the primary issues associated with district heating in the Old Town and developed a methodology to assess the effects of partial and full transitions to district heating in the historic quarter, as well as the challenges associated with these transitions. The methodology includes multiple-criteria decision analysis methods, scenario comparison by indicators, expert interviews, and a comprehensive review and analysis of the legislation. The current situation was compared to four other scenarios: very-easy-to-connect, easy-to-connect, and difficult-to-connect consumers, as well as when all buildings are connected to district heating. According to the results, switching to district heating reduces primary energy consumption by 16%. • Study shows how cities' historic centre can be converted to a district heating. • Challenges: higher qualification requirements for staff, additional archaeological research, narrow streets, need to use specific materials. • Switching of all consumers to DH will reduce primary energy consumption in Old Tallinn by 16%. • Potential DH consumers in historic centre are evaluated and ranked based by the availability. [ABSTRACT FROM AUTHOR]

At present, integrated energy system (IES) suffers high operating cost due to poor energy saving and low emission reduction and insufficient consumption of renewable energy though wind and solar energy production are abundant. Thus, a low-carbon economic operation model is proposed in this paper. This model combines the characteristics of flexible load on the demand side and operates jointly with combined heat and power (CHP), carbon capture system (CCS), and power to gas (P2G). It considers the combination of source-side scheduling and demand-side scheduling. Finally, the problem is solved using MATLAB/YALMIP to call GUROBI and the interior point method (IPOPT) based on Hessian matrix iteration. The results show that the reasonable scheduling of the flexible load on the demand side realizes the peak load shifting and reduces the peak load regulation pressure of the system. The operation mode of source-side CHP coupled with CCS and P2G improves the utilization of renewable energy and curtails the carbon emission of the system. The proposed model transaction cost and daily operating cost are less than the base case by 61.34% and 50.49%, respectively. • An optimization model of P2G, CCS, and CHP with the flexible load was developed. • Multi-energy coupling relationship in the integrated energy system was analyzed. • Different flexible power and heat load to smooth the load curve were considered. • The operation effects of IES under different operation modes were compared. [ABSTRACT FROM AUTHOR]

The safety of high-altitude environments is defined by temperature, humidity and oxygen concentration. This paper proposed a Heat and Oxygen Unit Pump (HOUP) system, and introduced its design principles, experimental apparatus and testing results in detail. Moreover, it analyzed the parameters of heat produced, air supply temperature, concentration of produced oxygen, and the temperature of air compressor, then compared the energy consumption, COP value, power and the HOEI (Heat and Oxygen Economic Index) value, a comprehensive economic benefit index designed by economic principles, when the oxygen production system and the heat production system operated independently or jointly. The preliminary research results showed that the HOUP system could fully utilize the afterheat of the air compressor, increased the produced heat by 5.5%–24.5% and the COP value by 21.4% compared with the traditional heat pump system. The HOUP system reduced energy consumption by 5.3%–14.9% for entire system, by 5.6%–31.1% for heat and by 4.7%–8.4% for oxygen production. Furthermore, HOUP system's HOEI was 455–972 under the conditions of oxygen production flow of 15-10SLM and room temperature of 24°C–30 °C, i.e., a 455-972-fold economic benefit could be gained. • Designed a machine (HOUP system) that can produce oxygen and heat at the same time. • The energy consumption of the HOUP system is reduced by 5.3%∼15.9%. • The COP value of the HOUP system is increased by 21.4%. • A new solution is provided for improving high-altitude living environment. [ABSTRACT FROM AUTHOR]

Continuous-flow microwave heating has been widely applied in liquid food processing, and the heating efficiency relies heavily on the dielectric property of loads with fixed dimensions in a certain cavity. Specifically, rectangular waveguides are widely applied, and straight pipes are usually inserted through the center of rectangular waveguides. However, maintaining high efficiency is always challenging since the dielectric property will vary with temperature. Therefore, a simple and cheap resonant structure is proposed in this paper to maintain high heating efficiency for loads with a large range of relative permittivity in both modeling and experiment. First, the straight pipe surrounded by metal rings in a rectangular waveguide with a short circuit terminal was introduced to concentrate the electric field in the pipe. Then, a multiphysics model was established to calculate the energy efficiency of various load permittivity. The position of the short circuit terminal and the dimensions of the metal ring were further optimized. Finally, energy efficiency experiments of different aqueous ethanol solutions and liquid foods and point temperature rise experiments of continuous-flow water were carried out, and the results showed that the proposed structure can be used to maintain high energy efficiency over large dielectric dynamic ranges compared with the conventional microwave heating system based on rectangular waveguides. Moreover, the effect of different parameters, the pipe permittivity, the pipe wall thickness and the metal ring gap, on the heating efficiency was discussed to show the robustness of the proposed structure. • A simple and low-cost resonant structure for high-efficiency microwave heating was proposed. • Metal rings were applied to enhance the electric field and concentrate the microwave energy. • High energy efficiency with various load permittivity was realized. [ABSTRACT FROM AUTHOR]

To improve the defrosting accuracy and the energy efficiency of the air-source heat pump (ASHP) under frosting and defrosting conditions, a novel Temperature–Humidity–Time (T–H–T) defrosting control method, based on a frosting map for the ASHP unit, is proposed in this paper. A field test was conducted for two heating seasons, to verify the feasibility and applicability of the T–H–T method. The advantages of the T–H–T method, compared to the conventional Temperature–Time (T–T) defrosting control method, are presented. In total, eight cases are shown in this paper. Cases 1 to 4 were chosen to reveal the T–H–T performance under different frosting conditions. It was found that no matter what kind of frosting conditions, defrosting was always initiated in a similar situation: ∼90% of the outdoor coil surface was covered by frost; the temperature difference between the compressor suction and discharge increased by ∼20%; and the heating capacity decreased by ∼30%. These results indicate that the T–H–T method can make an accurate decision under different frosting conditions. Cases 5a, 5b and Cases 6a, 6b were two groups of cases to compare the advantages of the T–H–T method against the conventional T–T method. Cases 5a and 5b were chosen for the non-frosting condition. It was found that the T–T method initiated the defrosting operation 31 times within 24 h. However, none of the defrosting operations was conducted for the T–H–T method. Cases 6a and 6b were chosen to compare these two methods under consecutive and variable frosting conditions. For the T–T method, 63% of the defrosting processes were found to be executed under conditions where defrosting was not necessary. However, for the T–H–T method, all the defrosting controls were found to be accurate and reasonable. These results indicated that the novel T–H–T method is suitable for the defrosting control of the ASHP, and has a more competitive performance than the conventional T–T method. [ABSTRACT FROM AUTHOR]

The dual heat source coupling modes of solar-ground source heat pump system (SGSHPS) directly determine its operation characteristics. In this paper, the thermal performance of a SGSHPS operated in different dual heat source coupling modes were studied experimentally. The unit COP, solar collecting efficiency and inlet and outlet temperatures of GHE were tested for various modes. The results show that for the combination operation mode, solar and ground heat source are dynamically coupled by the water tank and plate heat exchanger, and the average unit COP and collecting efficiency are 3.61 and 51.5%, respectively. For the water tank heat storage mode, the inlet water temperature of evaporator in the daytime stop mode of GSHP is 1.85 °C higher than daytime operation mode of GSHP, and the average unit COP and collecting efficiency are respectively 3.43 and 34.8%, 3.91and 34.9% for the daytime stop mode of GSHP and daytime operation mode of GSHP. For the ground heat storage mode, the ground temperature can be improved effectively for ground continuous heat storage mode and the outlet temperature of GHE can be increased significantly for ground intermittent heat storage mode. The average unit COP and collecting efficiency are 3.65 and 47.9%, 3.8 and 41.5% for the ground intermittent and continuous heat storage mode, respectively. A TRNSYS dynamical simulation model of the SGSHPS was established to explore the influences of key parameters on the system performance. The results indicate that the collector area and GHE number have evident influences on the system efficiency, but the impact of water tank volume is very small. The suitable collector area and GHE number are found to be 80 m 2 and 9, respectively, and the water tank volume should be set as small as possible with the permission of actual conditions. [ABSTRACT FROM AUTHOR]

Nowadays, the main two issues of heating ventilation and air conditioning (HVAC) are refrigerant alternative and system efficiency improvement. As a safe and environmental protective refrigerant, CO 2 has drawn a lot of attention these years. The improvement on its transcritical cycle efficiency has always been the study hotspot. On the basis of the traditional cycle system, this paper adds the internal heat exchangers (IHE) and pressure control devices into the system and optimizes the CO 2 transcritical system with the dual throttling device. Engineering equation solver is used to build each module in the system as an object-oriented model. The effects of the IHE and bypass valve on system performance are investigated. The performance and configuration of four CO 2 transcritical refrigeration cycles are analyzed and compared. Numerical studies also propose the formula expressing the relationship of the optimum high pressure, the gas-cooler CO 2 outlet temperature and the evaporation temperature under specific operating conditions. In addition, the modified system can significantly improve the performance of the system under the operating conditions below the optimum high pressure. This research has played an effective guiding and facilitating role for CO 2 transcritical refrigeration system development, optimization and improvement. [ABSTRACT FROM AUTHOR]

Utilizing the waste heat of exhausted steam in power plant as a new type of heat source is a key direction to achieve both energy-saving and clean urban heating. In order to recycle all the exhausted steam waste heat of multiple turbine units in designing condition, the authors’ research group proposed a new cascade heating system with multi-heat source and applied it in several air cooling power plants in China. This paper focused on the system integration improving and operation strategy formulating, the main studies included: (1) Established the calculation model of system heating characteristics, and analyzed the problems about energy efficiency of system and safety of air cooled condenser in full operating conditions. (2) Introduced the “equivalent electricity of heating” as the evaluation method of comprehensive energy efficiency of the new co-generation heating system. (3) Improved the integration of heating system to further realize energy cascade utilization between turbine units. (4) Aiming at the improved heating system, the comprehensive optimization ideas of operational parameters in full operating conditions were put forward. By above methods, on one hand the “equivalent electricity of heating” of the new co-generation heating system is decreased by 16%, the comprehensive energy efficiency of system is improved, on the other the freezing risk of air cooled condenser is relieved, the operation safety of system is improved. [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]

This paper compares the electricity, heating, and cooling sectors at national level for various European countries. Annual energy demands are compared for all 28 EU countries, while peak hourly demands are compared for four countries that vary significantly. The results indicate that the heat demand is currently the largest of the three demand types considered in terms of both annual and peak demands: it is the largest annual demand in 25 of the 28 EU countries, and it represents the largest peak demand in all four countries analysed. Electricity, heating, and cooling demands are all likely to change significantly in the future with increasing electrification, energy efficiency (e.g. building insulation), and improved comfort (especially for cooling). Some extreme scenarios are presented here to quantify the potential impact of these changes on the electricity sector, with results revealing that the demand for electricity could double compared to today, depending on how these changes occur. Considering the scale of additional electricity required to electrify future heating and cooling demands, heat pumps should be prioritised over electric heating and other alternatives, such as district heating and cooling, will likely be required to minimise the strain on the electricity grid in the future. [ABSTRACT FROM AUTHOR]

During the master planning of neighbourhoods, design decisions related to the urban layout and typology affect the building form and availability of solar radiation considerably. The influence of those decisions on the energy demand for heating is often neglected however because appropriate energy simulation tools are lacking. This paper proposes a simple and accurate design tool to assess the solar gains and heating energy demand in buildings during the master planning phase of neighbourhoods. Detailed information on building geometry, constituting building elements and solar obstructions, is extracted from a 3D neighbourhood model using a plugin implemented in the modelling software SketchUp. This information is used to assess the heating energy demand of the buildings in the neighbourhood based on the dynamic Equivalent Heating Degree Day (dEHDD) method. Furthermore, the associated financial and environmental impacts are calculated based on an integrated life cycle approach, combining Life Cycle Costing (LCC) and Environmental Life Cycle Assessment (E-LCA) respectively. The design tool proposed is implemented for the Belgian context and used to analyse a number of schematic residential neighbourhood models with diverse built densities. The analysis reveals substantial differences in heating energy demand, life cycle financial and environmental costs. Neighbourhoods with a high built density and compact building types have a lower heating energy demand with potential reductions of up to 40% compared to neighbourhoods with a low built density and detached building types. [ABSTRACT FROM AUTHOR]

Heat loss from rotary kilns accounts for certain amounts of the total energy consumption in chemical and metallurgical industries. To reduce the heat loss, a parallel and a series-parallel heat recovery systems with nine heat recovery exchangers are proposed to preheat the cold water in this paper. Experimental measurements are carried out to determine the heat transfer coefficient equations of each heat recovery exchanger. Then, the heat recovery systems are analyzed to deduce the mathematic relation between the design parameters and the system requirements, i.e. the temperatures and heat transfer rates of the nine heat recovery exchangers. The total heat transfer area, the total power consumption and the entropy generation due to heat transfer and fluid flow are set as the objective functions in four multi-objective optimization (MOO) cases. With the aid of the genetic algorithm in the Matlab 2015, the optimized operational and structural parameters are obtained. Finally, the MOO results are compared with that of the single objective optimization (SOO) method and the original values. The optimization results show that the MOO method are more suitable for the operational parameters design of the heat recovery systems compared with the SOO method. The required total heat transfer area and the total power consumption are decreased by at least 12.1% and 13.7%, respectively. Besides, as the entropy generation due to heat transfer and fluid flow decrease in the MOO cases, the corresponding heat transfer area and power consumption of the heat recovery system decrease, respectively. [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]

Forecasting the short-term future energy demand in buildings and districts is a vital component towards the optimization of energy use and consequently the reduction in greenhouse gas emissions. This paper explores artificial intelligence approaches applied to estimate the future heating load in a district heating system. A distinction is made within thisd work between a prediction and forecasting based approach; a comparison is then accomplished by applying each method with prominent Machine Learning and Deep Learning based algorithms to estimate the future heating demand over 6 h and 24 h ahead. This analysis used available data from a Canadian district heating system in Quebec and actual weather forecasts obtained from Canadian meteorological services. All models within this work applied a grid search in order to calibrate their respective hyperparameters. Results of this work indicated that the prediction-based approach (with forecasted inputs) obtained a higher accuracy than the forecasting approach. All the machine learning models obtained good accuracy with errors not exceeding 16% CV(RMSE) and closer to 10% CV(RMSE) for the top performing models. Furthermore, the LSTM and XGBoost were consistently among the top performing algorithms and provided good performance over a variety of hyperparameters. The biggest difference between the two algorithms was the computational times; it was observed that the XGBoost was significantly faster to train. • Artificial Intelligence models are investigated to forecast district heating demand. • Prediction and forecasting based approaches are compared. • Model performance is estimated using accuracy, training time and stability. • The prediction approach using forecasted inputs shows slightly better results. • LSTM and XGBoost models outperform other techniques with an error of 11%. [ABSTRACT FROM AUTHOR]

Although electric power networks and district heating networks are physically coupled, they are not operated in a coordinated manner. With increasing penetration of renewable energy sources, a coordinated market-based operation of the two networks can yield significant advantages, as reduced need for grid reinforcements, by optimizing the power flows in the coupled systems. Transactive control has been developed as a promising approach based on market and control mechanisms to coordinate supply and demand in energy systems, which when applied to power systems is being referred to as transactive energy. However, this approach has not been fully investigated in the context of market-based operation of coupled electric power and district heating networks. Therefore, this paper proposes a transactive control approach to coordinate flexible producers and consumers while taking into account the operational aspects of both networks, for the benefit of all participants and considering their privacy. A nonlinear model predictive control approach is applied in this work to maximize the social welfare of both networks, taking into account system operational limits, while reducing losses and considering system dynamics and forecasted power supply and demand of inflexible producers and consumers. A subtle approximation of the operational optimization problem is used to enable the practical application of the proposed approach in real time. The presented technique is implemented, tested, and demonstrated in a realistic test system, illustrating its benefits. • Transactive control design for coupled electric power and district heating networks. • Development and application of an accurate and computationally efficient system model. • Technical and economic optimal system operation considering participant privacy. [ABSTRACT FROM AUTHOR]

Abstract: Microturbines offer new perspectives in small-scale heat and power production however their profitability depends strongly on the yearly amount of running hours. The non-continuous heat demand often leads to a reduction in running hours. This paper proposes an alternative by recuperating the lost thermal power through the injection of heated water in the micro Gas Turbine (mGT). Water injection is considered a successful way to increase power and efficiency in industrial gas turbines and similar effects are expected for microturbines. This paper reports on a series of simulations of water injection performed on a Turbec T100 mGT. The goal of this study was to investigate the potential of water injection in the mGT cycle using an adiabatic black box method in the Aspen® process simulation tool. Past experiments with steam injection on the T100 demonstrated the potential of introducing steam/water in the microturbine cycle. Calculations revealed that the key parameters for maximum heat recuperation are stack and pinch temperature. Simulations showed that most of the exhaust heat can be recovered through injection of heated water after the compressor, resulting in an 18% decrease in fuel consumption and an absolute increase in electrical efficiency of 7%. [Copyright &y& Elsevier]

[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 system engineering based on photovoltaic thermal heat pump was constructed. • A new idea for the energy-saving reconstruction of district heating was introduced. • The prediction model of system heating performance was established and optimized. • The equivalent electricity consumption of heating was defined. • The economic performance of energy-saving reconstruction was studied. Actively promoting the reconstruction of clean heating is the key direction of the "Planning for clean heating in winter in northern China (2017–2021)". The photovoltaic thermal heat pump system was introduced in this paper to improve the comprehensive energy efficiency and reduce the operation energy consumption of the heat source system, which provided a new idea for the energy saving reconstruction of clean district heating. In order to verify the feasibility of the energy saving reconstruction by photovoltaic thermal heat pump, following studies were carried out in this paper: First, the integrated energy system engineering based on photovoltaic thermal heat pump was constructed to study the heating performance of the system in winter. Subsequently, the prediction model of heating performance based on back propagation neural network was established and optimized to simulate the heating performance throughout the year. Then, the calculation model of district heating system was established and the evaluation method of system operation energy efficiency and economic performance based on "equivalent electricity consumption of heating" was introduced. Finally, a residential area of Dalian was taking as an example to study the economic performance of energy saving reconstruction of district heating system based on three conventional heat sources by photovoltaic thermal heat pump. The results showed that after the capacity expansion and energy saving reconstruction based on photovoltaic thermal heat pump were conducted, the payback period of energy saving reconstruction investment was 5 years. Besides, with the increase of the configuration ratio of photovoltaic in the system from 1 to 2, the payback period was further shortened to 3 years. [ABSTRACT FROM AUTHOR]

The building sector accounts for significant portion of total final energy use in most countries. One way to reduce significantly building energy consumption is to adopt energy efficiency technologies and strategies. Due to environmental concerns and high cost of energy in recent years there has been a renewed interest in building energy efficiency. Passive House (PH) standard provides a cost-efficient way of minimizing energy demand of buildings in accordance with global principle of sustainability. However, it is ongoing challenge to improve building energy efficiency without compromising indoor environmental quality. The objective of this paper is to review the interactions between energy performance and indoor environment quality in buildings with PH standard, considering parametric sensitivity study including effects of diverse parameters on PH building performance. Passive House technologies including heat and cooling recovery ventilation, pre heating/cooling fresh air, pre-ventilation and passive cooling are presented considering different weather conditions. Thermal comfort represented by recommended thermal range and comfort zone and indoor air quality indicated by CO2 concentration have been numerically and experimentally analysed. The simulation and measurement results illuminate that it is possible to realize energy efficiency and favourable indoor environment in PH buildings at the same time. [ABSTRACT FROM AUTHOR]

During startup or normal operations, tube monitoring systems for steam boilers can considerably improve efficiency and reliability in thermal power plants (TPPs). Although several attempts have been made to detect and locate boiler tube leaks, what seems to be lacking is the study for tube plugging, one of the fundamental causes of the leaks and other tube failures. Scale and deposit formations on inner surfaces of tubes cause the tubes to be plugged. Although the formations can be suppressed and removed by chemical treatments for boiler water and steam blowing during startup procedures, it is still difficult to monitor and prevent tube plugging during startup or normal operations. In this paper, a novel plugged tube detection and identification approach is proposed for final super heater (FSH) tube banks. Principal component analysis is applied to tube temperature data for plugging detection and identification. The data are collected from thermocouples installed on the FSH outlet header section. To identify plugged tubes, contribution analysis and the characteristics of plugged tube temperatures are employed. To verify the performance of the proposed method, tube temperature data from an 870 MW supercritical coal-fired TPP are used. The experiment results show that the proposed method can successfully detect and identify plugged tubes. The proposed method can help to decide how many times steam blowing should be performed, whether startup procedures should be delayed or stopped, and which tubes should be maintained. Furthermore, severe tube failures can be prevented by avoiding damage from overheating due to tube plugging. [ABSTRACT FROM AUTHOR]

In a central heating, ventilation, and air conditioning (HVAC) system, the set-points for several local control loops have a significant influence on the overall energy performance of the system. Real-time optimization (RtOpt) of those set-points has therefore been widely studied. However, due to the nonlinear dynamics of the HVAC system as well as the constraints associated with the system operation, real-time optimization always suffers from a heavy on-line computational load when those set-points are optimized simultaneously. To overcome this problem, multiplexed real-time optimization (MRtOpt) has been developed, which optimizes only one set-point at a time but with a faster optimization frequency. Because frequently resetting the set-points introduces artificial disturbances into the local control loops and may deteriorate the system stability, this paper presents a study to enhance the system stability of the multiplexed real-time optimization by integrating a degree of freedom (DOF) based set-point reset to renew the set-points instead of the conventional step-change set-point reset. The control performance of the integrated strategy was investigated using case studies. The results showed that around 10% of the energy saving was achieved by the proposed method compared with a method without real-time optimization. When compared with the conventional real-time optimization method, the proposed method resulted in around 70% computational load reduction, and over 26% reduction in the tracking errors of the local control loops. [ABSTRACT FROM AUTHOR]