Building Heating Systems Research Articles

Application of the air-pipe rack heat exchanger heating system in residential buildings of Guangzhou

In recent years, underground pipe racks have been extensively constructed in urban areas of China for laying municipal pipelines. As the corridor has a tunnel-shaped underground structure, it can preheat the outdoor air entering from outside in winter. In this study, an underground air-pipe rack heat exchanger (APRHE) system used for residential heating in Xiaoguwei Island, Guangzhou was tested for its thermal performance in winter. Results show that the preheating performance of the APRHE was remarkable and its performance was better at night than during the day. The APRHEs of 150-m long comprehensive and cable trenches can preheat and maintain the air temperature at 21.6 °C and 22.4 °C at night, which were 12.0 °C and 12.8 °C higher than that of the outdoor air, respectively. Their average heating power at night reached 23.9 kW and 24.6 kW, respectively, and the average daily heating energy reached 590.7 kWh and 603.2 kWh, respectively. The preheating performance of the APRHE and its feature of better air quality at night than that during daytime render it a good candidate for residential heating. It is recommended that the preheating length could be set at 100 m. The static and dynamic payback periods of the APRHE residential heating system were estimated at 3.17 and 4.37 years, respectively. The air quality in the pipe rack under the calm wind condition however failed to meet the specifications completely, with the air quality at night being better than that during the day due to the difference in the emission of vehicle exhaust.

Numerical investigation of serpentine earth-to-air heat exchanger for passive building heating systems by recovery criteria

This paper investigates the performance of the earth-to-air heat exchanger (EAHE) system in the winter for Mashhad. A three-dimensional model of novel serpentine geometry for use in the passive building heating system is proposed. A new and visual method of recovery analysis is performed for regaining the soil energy by considering a period of time to stop the system. The thermal performance of the system is evaluated by analyzing the derating factor, knee point, and heat transfer evaluation criteria for a serpentine model of EAHE. Results demonstrate that the thermal conductivity of the soil and the duration of EAHE's continuous operation has a significant impact on its transient thermal performance. By employing soil thermal conductivities of 1, 2, and 4 W/m.K, the temperature of the outlet reduced 21 %, 12 %, and 6 %, respectively. Finally, the results indicate the highly better performance of the system in soils with higher thermal conductivity during long-term. The temperature of the outlet air in the 24-hours operation mode decreases compared with the 1-hour operation mode. A new method of recovery analysis is performed for regaining soil energy. This paper aims to develop a new model of EAHE system to maximize the energy use of buildings.

Analysis of Hydronic Heating and Cooling Systems in Commercial Buildings Using CBECS Microdata

Analysis of Hydronic Heating and Cooling Systems in Commercial Buildings Using CBECS Microdata

Experimental and numerical study on the thermal energy storage performance of a novel phase-change material for radiant floor heating systems

Thermal energy storage shows great potential for improving the energy performance of building heating systems. Phase-change materials are a promising type of storage medium for building envelopes due to their high storage capacity. However, the low thermal conductivity and easy leakage of the hydrated salts inhibit their practical application. In this study, sodium acetate trihydrate–acetamide/modified expanded graphite was prepared as a novel thermal-stable storage medium for space heating applications. Leakage protection tests showed that modified expanded graphite presented a better compatibility with hydrated salts. The thermal conductivity of the novel composite reached 1.87 W/m∙K, 4.5 times higher than that of the pristine mixture. Moreover, the PCM exhibited a great thermal reliability with a high latent heat of 161.9 kJ/kg and an acceptable supercooling degree of 2.2 °C after cycling. The thermal performance of radiant floor heating systems with different layer structures was evaluated. The heat storage and release of the storage medium were beneficial for reducing the temperature fluctuation and improving the indoor comfort. The operation cost of the system without the storage medium was 73.1% higher than that with the storage medium. This performance enhancement suggests that the novel composite is a competitive candidate for heating applications.

High Efficiency Hybrid Radiant and Heat Pump Heating Plants for Industrial Buildings: An Energy Analysis

A hybrid condensing radiant tubes system coupled to a heat pump to heat a typical industrial building was modeled in three climatic zones of Italy using dynamic simulation software. The heating system was set up by radiant tubes and an air heating system with terminals placed in the building supplied by hot water produced by the condensation of the exhausted of the radiant tubes and by a heat pump with external air heat source. An optimization of the main parameters (nominal power of the heat pump, bivalent temperature in alternative bivalent operation, and peak power of the photovoltaic system) was carried out on the basis of energy performance of the hybrid heating system. The optimal configuration of the hybrid heating system that minimizes the annual amount of total non-renewable primary energy and maximizes the non-renewable primary energy ratio was compared with traditional heating systems for industrial buildings. The energy savings of this innovative solution vary in the range of 40%-80% depending on the climate and the configuration of the system.

RESEARCH OF TECHNOLOGICAL POSSIBILITIES OF HEAT PUMPS’ APPLICATION IN DISTRICT HEATING OF RESIDENTIAL BUILDINGS

The main users of district heating (DH) systems are multi-apartment buildings – 53% of these buildings in Lithuania are supplied with heat from DH systems. Heating systems in buildings are the largest final consumer of energy, accounting for almost half of total energy consumption in many European countries. One of the measures planned for the Lithuanian energy policy in the heat sector of renewable energy sources (RES) until 2030 is the installation of heat pumps (HP) in the DH networks. The purpose of the study is to evaluate the technological possibilities of integrating HP into existing buildings to evaluate the low temperature heat supply. To evaluate the potential temperature lowering of the building heating system, a graph of the lowest possible building heating system temperatures is set, according to which the heat pump for the heating substation is selected, which would raise the temperature of the heat carrier supplied from DH networks to the required temperature for the heating and hot water systems of the building. Applying thermodynamic analysis, a mathematical model is developed that evaluates the ability of the HP to raise the temperature of the supplied heat carrier at the heat substation and determines the energy efficiency of such a solution. During the simulation, two alternatives of constant (regardless of outdoor air temperature) heat carrier temperatures supplied from DH networks were considered: 60 °C (alternative A) and 55 °C (alternative B). To adapt the most appropriate option for the integration of HP, it would be appropriate to combine both alternatives, i. y. to supply 60 °C from the DH network in the cold period of the year and 55 °C in the warm period of the year.

Embedded Real-Time Clothing Classifier Using One-Stage Methods for Saving Energy in Thermostats

Energy-saving is a mandatory research topic since the growing population demands additional energy yearly. Moreover, climate change requires more attention to reduce the impact of generating more CO2. As a result, some new research areas need to be explored to create innovative energy-saving alternatives in electrical devices that have high energy consumption. One research area of interest is the computer visual classification for reducing energy consumption and keeping thermal comfort in thermostats. Usually, connected thermostats obrtain information from sensors for detecting persons and scheduling autonomous operations to save energy. However, there is a lack of knowledge of how computer vision can be deployed in embedded digital systems to analyze clothing insulation in connected thermostats to reduce energy consumption and keep thermal comfort. The clothing classification algorithm embedded in a digital system for saving energy could be a companion device in connected thermostats to obtain the clothing insulation. Currently, there is no connected thermostat in the market using complementary computer visual classification systems to analyze the clothing insulation factor. Hence, this proposal aims to develop and evaluate an embedded real-time clothing classifier that could help to improve the efficiency of heating and ventilation air conditioning systems in homes or buildings. This paper compares six different one-stage object detection and classification algorithms trained with a small custom dataset in two embedded systems and a personal computer to compare the models. In addition, the paper describes how the classifier could interact with the thermostat to tune the temperature set point to save energy and keep thermal comfort. The results confirm that the proposed real-time clothing classifier could be implemented as a companion device in connected thermostats to provide additional information to end-users about making decisions on saving energy.

Heat pump inspections result in large energy savings when a pre-selection of households is performed: A promising use case of smart meter data

Heat pumps play an important role in the energy transition. They can extract renewable energy from the air or ground and increasingly replace fossil heating systems in buildings. In operation, however, heat pumps often consume more electricity than necessary due to incorrect settings and installation deficiencies. Although many setting and installation issues are easy to fix, problems often go unnoticed, and the saving potential from quick fixes remains unclear. In a study with 297 Swiss households (41 treatment, 256 control) running for four years, we investigated an energy efficiency campaign in which the treatment group received a professional heat pump inspection and user training. We found considerable heterogeneity with respect to the savings achieved. We derived two criteria based on smart meter data that enable utilities to identify relevant households and thus boost the impact of such efficiency campaigns: For example, pre-selecting half of the households based on available information results in average savings of 1,805 kWh (15.2%) per year and household in the high-potential group compared to no savings in the low-potential group. Thus, heat pump inspections among pre-selected households can lead to large, cost-effective electricity savings, and we show that common smart meter data makes such pre-selection feasible.

Cost-effective occupation dependant infrared zonal heating system for operational university buildings

Recent legislations have necessitated policies for carbon print reduction. Buildings and in particular space heating are major energy consumers and responsible for over 34% of carbon print. This work presents a method of heating only certain parts of the building using far infrared (FIR) heating. This study gives an overview on the application of infrared radiation in heating by modern methods in tune and compatibility with climate developments for the public spaces in this decade. The case study is on a university lecture theatre and the space is split up into varyingly sized zones which enable different parts of the room to be heated depending on the time and occupation of the zone. The potential to heat each zone with FIR is implemented which runs according to the machine learning algorithm (MLA) through a practical study of real CO2 data collection and validation. This allows heating to start running before the zone(s) is occupied to optimise thermal comfort. Results show that occupation zone FIR heating saves an average of 11.175kWh through various occupations compared to the currently equipped convection wall mounted radiators. Occupation forecasting of the room using random forest machine learning has an accuracy of 97.75% for 15-minutes intervals of a day. Cost analysis for the proposed occupation heating show savings of up to 76% and 14.6% compared to convection electric and gas heating respectively. FIR provides a more efficient method of heating with the capacity for zonal implementation. The results in this research demonstrate the feasibility of FIR zonal heating for non-domestic applications.

On energy-efficient HVAC operation with Model Predictive Control: A multiple climate zone study

This paper aims to quantify the performance of Model Predictive Control (MPC) for a typical commercial building heating, ventilation and air conditioning (HVAC) system across a wide range of climate and weather conditions. The motivation of the study comes from the fact that although there is a large body of work on MPC for HVAC systems, there is a lack of studies that examine the range of possible performance of MPC, in terms of both energy savings and maintaining indoor climate (temperature and humidity) as a function of outdoor weather. A challenge in conducting such a study is developing an MPC controller that can be used in a wide range of weather. The root cause of this challenge is the need for a tractable cooling and dehumidification coil model that can be used by the MPC controller, since the coil may operate in quite distinct modes depending on weather. We present such an MPC controller, and then leverage it to conduct an extensive simulation campaign for fourteen climate zones in the United States and four weather conditions (winter, spring, summer, and fall) in each climate zone. The performance of the proposed controller is compared with not only a rule-based baseline controller but also with a simpler MPC controller that ignores humidity and latent heat considerations. There are several results the arise from this comparative study. One such result is that energy savings from MPC over baseline can vary dramatically based on climate and season. Another is that the effect of ignoring humidity in the MPC formulation can lead to poor indoor humidity control more in milder weather rather than in hot weather. The results from this study can help practitioners and researchers assess costs and benefits of proposed MPC formulations for HVAC control.

Discrete-Time-Distributed Adaptive ILC With Nonrepetitive Uncertainties and Applications to Building HVAC Systems

Aiming to addressing the nonrepetitive uncertainties of multiagent systems, this work proposes a discrete-time-distributed adaptive iterative learning control (DDAILC) scheme for an output consensus problem, where two fundamental requirements in the traditional distributed iterative learning control (ILC) methods, i.e., the identical initial states and the repetitive desired trajectories, are removed. Furthermore, the algorithm design and analysis are directly aimed at discrete-time nonlinear multiagent systems, rather than continuous-time ones, to meet the needs of practical implementations. The iteration-varying trajectory of the virtual leader is included in the learning control protocol for a compensation. The adaptive parameter-updating law works along the iteration dimension by using a general consensus error that contains the output data of adjacent agents. To ensure the estimation of the control gain to be nonzero, a semisaturator is utilized in the parameter-updating law. The convergence of the output consensus is shown rigorously. Both numerical and practical examples are used to test the theoretical results. Moreover, the DDAILC efficiently improves performance of the building heating, ventilation, and air conditioning (HVAC) system by utilizing both the distributed topology and the repetitive dynamic characteristic.

An Analytical Model for the Impact of Building Control and Automation Upgrade on Space Heating Energy Efficiency

Intelligent building management systems are proven to lead to energy savings and are an integral component of smart buildings. The procedures developed in the EN standards describe the methodology for calculating the energy savings achieved by improving the automation and control levels of separate services in building systems. However, although this method is used in practice, it is rarely applied or investigated by the research community. Typically, energy savings resulting from a single automation improvement intervention in a building heating system are observed, while the holistic view of combined automation upgrades is not considered. Therefore, the purpose of this study was to assess the energy savings resulting from several upgrades to control levels in the heating system components of the building. In addition, this research provides a rationale for the impact of multiple automation and control options for heating systems as well as examines the difference in energy savings. Finally, an analytical model is developed and demonstrated to assess the feasibility of building automation and control upgrades, by determining the allowed investment according to a set of predefined indicators.

Dynamic Calibration Method of Sensor Drift Fault in HVAC System Based on Bayesian Inference.

Sensor drift fault calibration is essential to maintain the operation of heating, ventilation and air conditioning systems (HVAC) in buildings. Bayesian inference (BI) is becoming more and more popular as a commonly used sensor fault calibration method. However, this method focused mainly on sensor bias fault, and it could be difficult to calibrate drift fault that changes with time. Therefore, a dynamic calibration method for sensor drift fault of HVAC systems based on BI is developed. Taking the drift fault calibration of the chilled water supply temperature sensor of the chiller as an example, the performance of the proposed dynamic calibration method is evaluated. Results show that the combination of the Exponentially Weighted Moving-Average (EWMA) method with high detection accuracy and the proposed BI dynamic calibration method can effectively improve the calibration accuracy of drift fault, and the Mean Absolute Percentage Error (MAPE) value between the calibrated and normal data is less than 5%.

Distributed Optimal Control for HVAC Systems Adopting Edge Computing—Strategy, Implementation, and Experimental Validation

Internet of Things (IoT) has found increasing applications in industry, including the building automation field. Edge computing, a distributed computing paradigm using the computing resources of edge devices that are close to the sources of data, is an effective means for dealing with the network traffic caused by the centralized structure and rapid growth of IoT devices. This article proposes a distributed optimal control strategy for building heating, ventilation, and air conditioning systems adopting edge computing. The proposed distributed optimal control strategy is designed for the deployment on the smart sensor nodes in the IoT-enabled field control networks of building automation systems. A complex optimization task with high computational complexity is decomposed into several simple tasks, which can be handled by coordinating the agents implemented on the sensor nodes. In this manner, the computing resources of smart sensors are used collectively to optimize the subsystem operation locally. Compared with centralized optimal control strategies, the distributed form of the proposed strategy allows better generality and flexibility. A hardware-in-the-loop simulator is constructed as a realistic test environment for real control devices. Being implemented on a wireless IoT sensor network integrated in the simulator, the applicability and the performance of the proposed strategy are validated and evaluated. The experience and test results show that the IoT sensing network has the capacity to implement the distributed optimal control strategy and handle the decomposed optimization tasks effectively. The energy performance of the proposed distributed optimal control strategy is almost the same as that of the perfect solutions.

Optimization of heating efficiency of buildings above underground coal mines by infrared heaters

Purpose. To optimize the energy and economic efficiency of heating system of ground structures of coal mines with infrared heaters due to the rational choice of technical parameters of heating devices and their operating conditions, namely, the irradiation intensity of the floor q, thermal power of the heater Q, blackness degree of the floor surface and the height of installation H of infrared heaters. To achieve this goal, the task was to conduct theoretical and experimental studies on infrared heaters NL-12R of heating system of a building above underground coal mines during its thermal modernization. Methodology. At applying radiant heating systems, infrared heaters provide local heating of the working area of the buildings above underground coal mines. As a result, the necessary temperature conditions are maintained in the buildings above underground coal mines and there is a possibility of creating a local microclimate. A multifactorial experiment was performed taking into account the interaction of factors. The results of the study are presented in graphical and analytical forms. In addition, an analytical method was used to optimize parameters and operating conditions of the radiant heating system with infrared heaters NL-12R, and their number in the system of combined heating of buildings above underground coal mines is optimized. Findings. According to the experimental results, dependence of the relative floor temperature on the intensity of floor irradiation q, thermal power of the heater Q, blackness degree of the floor surface floor and the height H of infrared heaters location was determined. The results are presented in the form of graphs and nomograms, as well as approximated by their analytical equations. The annual economic effect of the optimal variant of combined heating system due to use the maximum number of infrared heaters NL-12R is 39.4 Euro/year provided that the installation of infrared heaters NL-12R with a power of Q = 1200 W in the number of 5 pcs. Originality. Optimization of energy and economic efficiency of heating system of buildings above underground coal mines by infrared heaters NL-12R, due to the rational choice of technical parameters of heating devices and conditions of their operation, was carried out by the analytical method. Practical value. Results of optimization of thermal and economic parameters of operation of the combined heating system of buildings above underground coal mines with installation of infrared heaters NL-12R with power Q = 1200 W proved the efficiency of combined heating of above-ground structures and the achievement of the annual economic effect of 39.4 Euro/year.

Study of the flat plate solar collector's efficiency for sustainable and renewable energy management in a building by a phase change material: Containing paraffin-wax/Graphene and Paraffin-wax/graphene oxide carbon-based fluids

Energy management in a building is to control and lessen the energy consumption, to decrease both costs and carbon emissions. Building-integrated thermal systems are adept to produce heat. Various scenarios have been planned to integrate heat into a building formation to enhance performance of entity system, supply indoor heating, and provide hot water. Concept backside Flat-plate Solar collector is that Sun warmth the set of tubes. This surface collects as much energy as preferable, and then water heats by this energy. This study aims to compare the Energy efficiency between phase change materials (PCMs) containing Paraffin-wax/Graphene and Paraffin-wax/Graphene Oxide carbon-based nanofluids for renewable, clean, green and sustainable energy systems such as Flat Plate Solar Collectors by applying these PCMs in Buildings heating systems. Results showed that, Thermal conductivity of both Graphene/P-wax and Graphene Oxide/P-wax was enhanced in comparison with Paraffin. Also, trend of Graphene showed better thermal performance.

ОЦЕНКА ВОЗМОЖНОСТИ СОЛНЕЧНОГО ТЕПЛОСНАБЖЕНИЯ С ИСПОЛЬЗОВАНИЕМ ВОЗДУШНОГО ТЕПЛОВОГО НАСОСА

Solar energy is one of the sources of renewable energy. However, during the cold season in Russia, the use of solar energy is difficult due to low outdoor air temperatures. The purpose of this article is to analyze the possibility of energy saving when using solar energy for the heating system of an individual residential building in Vladivostok. The latitude of the city is 43 °, but the estimated temperature for the design of heating is -22 ° C. This greatly complicates the use of solar heat. The possibility of accumulation of low-potential heat in a specially equipped outhouse (greenhouse) for conversion by a thermal air-water pump is analyzed in order to use it for heating needs in the future. Two constructions are considered as the finishing material of the extension: a two-layer polycarbonate with an air layer and an energy-saving double-glazed window. The calculation shows that in the coldest month is January, the potential of solar thermal energy is 14 %–37 % of the required heat demand, depending on the material used in the construction of the extension. In March and April, excess heat is generated. It can be used for hot water supply needs. Thus, for an individual residential building, the use of solar heat accumulated in a greenhouse extension is relevant as an additional source of heat for the heating system.

Using of heat thermal storage of PCM and solar energy for distributed clean building heating: A multi-level scale-up research

Solar energy coupled with electric heat storage is a promising energy saving technology for distributed building heating. Energy saving performance of this technology used in buildings has been widely investigated by prototype-scale experiments and numerical assessments. However, the commercial and economic feasibility of this technology during the operational phase of a real building have not been proven yet. This study conducted a comprehensive techno-economic analysis of the electric heat storage system coupled with solar energy installed in a three-story office building (2000 m2 heating area) in Tianjin, China. The electric heat storage system with the heat storage capacity of 1274.8 MJ was installed on the first floor of the building. The solar collector system with a total heat collection area of 160 m2 was installed on the roof of the building. Meanwhile, the long short-term memory was used to predict the heat gain of solar collector in order to adjust the quantity of storage heat of storage device. The results indicated that the prepared storage medium possessed an excellent thermal property with a total heat storage capacity of 448.8 kJ/kg within 50–150 °C. The average thermal efficiency of vacuum tube solar collector was 51.3%, its heat gain per square meter per day was 6.5 MJ. The use of the solar radiation prediction model stabilized thermal efficiency of heat storage reservoir at 95.8%. The specific operational cost of this system within an entire heating season was 15.6 renminbi (RMB)/m2/season. Distribute clean building heating (DCBH) system can save up to 61% of heating cost compared to the centralized heating. The results showed a great application potential of combination of electric heat storage and solar energy based on solar energy prediction for the heat dispatch of distributed building heating.

A hierarchical layout approach for underfloor heating systems in single-family residential buildings

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.

Integration of Heat Pumps in Buildings and District Heating Systems—Evaluation on a Building and Energy System Level

The use of heat pumps in buildings is one of the best and often the only option for the decarbonization of the building stock. District heating seems a promising solution in urban areas and in existing buildings when the use of heat pumps is restricted and also technically and economically challenging (source exploitation, space restrictions, sound emissions, etc.). Heat pumps can be integrated in various ways in buildings and district heating systems: large central high-temperature heat pumps in district heating, medium-size heat pumps block- or building-wise or small heat pumps decentral apartment-wise. The best option depends on the individual district heating CO2 emissions and the electricity mix as well as on the perspective of the building owner versus that one of the district heating system and its future development. Austrian examples of district heating systems and different variants of integrating heat pumps are investigated in a comprehensive way by means of an energetic and environmental simulation-based analysis. This assessment includes a detailed investigation of the capabilities of the booster heat pump to increase the PV own-consumption and is also expanded to include various scenarios for the development of the electricity mix and the decarbonisation of district heating.