Building Heating Systems Research Articles

Analysis of the influence of thermal insulation parameters on the effectiveness of enclosing structures and building heating systems

The results of thermal engineering calculations of external multilayer enclosing structures of buildings and the thermal power of the heating system of residential buildings are presented, including calculations of temperature fields and partial pressures of water vapor at various parameters of structural layers and thermal insulation layers. Variants are considered and an assessment is given of the variation of parameters and the different location of thermal insulation in external multilayer fences for changes in temperature fields and partial pressures of water vapor in the fence, as well as for changes in the thermal power of the heating system of the building premises for two climatological design areas. The calculations were performed according to the methodology presented below using a specially developed computer program.

New generalized expressions for forced convective heat transfer coefficients across the flat plate

This study presents a novel generalized model for forced convective heat transfer coefficients (CHTC) over flat plates, addressing key limitations in existing models. Current expressions often provide averaged values and fail to capture the local variations in heat transfer, leading to inaccuracies, particularly in transitional zones. Moreover, there is no consensus on boundary layer classifications, which further complicates the development of reliable CHTC models. To address these issues, we conduct extensive CFD simulations to systematically analyze the combined effects of plate length (L), wind velocity (v), position along the plate (x), and temperature difference (Δt) on local CHTC. The simulations span a wide range of conditions (0.25 m ≤ L ≤ 8 m, 3 m/s ≤ v ≤ 25 m/s, and 5 °C ≤ Δt ≤ 80 °C), creating a comprehensive database of local CHTC values. Based on this data, a new generalized CHTC expression is derived as a function of L, v, x, and Δt, accurately predicting CHTC across laminar, transitional, and turbulent zones of flat plats. The accuracy of proposed CHTC expression is verified through thorough in-sample and out-of-sample evaluations, achieving R2 values between 0.973 and 0.999, with maximum deviations ranging from 2.6 % to 8.5 %. These research methods and conclusions can provide valuable references for optimizing thermal processes in applications such as industrial heat exchangers, electronics cooling, and building heating systems, where precise heat transfer modeling is critical for enhancing efficiency and system design.

A Review of the Building Heating System Integrated with the Heat Pipe

The heat pipe (HP) is widely applied in the thermal management field at present. In order to make use of the low-grade and renewable energies to maintain building thermal comfort in the heating season, more and more studies with respect to improving the thermal performance of the building heating system integrated with the HP (BHSIHP), such as the floor heating system integrated with the HP (FHSIHP), the thermal storage wall heating system integrated with the HP (TSWIHP), conventional wall integrated with the HP (WIHP) and radiator heating system integrated with the HP (RHSIHP), are conducted. This paper aims to summarize different types of HPs applied in the building heating system and offers an overview of the thermal performance improvement for the BHSIHP. The thermal response, thermal conductivity, thermal resistance, heat capacity, heat transfer coefficient, temperature distribution, thermal storage and heat release capacity are always selected to investigate characteristics of the BHSIHP. Results show that the thermal performance of the FHSIHP, the TSWIHP, the WIHP and the RHSIHP is more outstanding than that of the conventional heating system. The thermal performance of the BHSIHP is affected by heat source temperature, installation tilt angle, working fluid, and filling ratio of the HP. The heat source temperature, which positively affects the performance of the BHSIHP, is crucial for the selection of the working fluid and filling ratio. However, the performance of the BHSIHP is increased first and then decreased with the increase of the installation tilt angle. The optimal filling ratio of the working fluid has been proven not to be a fixed value.

Dyna-PINN: Physics-informed deep dyna-q reinforcement learning for intelligent control of building heating system in low-diversity training data regimes

This paper introduces Dyna-PINN, a novel physics-informed Deep Dyna-Q (DDQ) reinforcement learning (RL) approach, designed to address the data-intensive training requirements and model-agnostic nature of the conventional model-free RL methods. The DDQ approach blends model-based and model-free elements to enhance both learning and decision-making processes. By utilizing a physics-informed neural network (PINN) based model, our method enriches the learning process with physical information, enhancing the agent's planning capabilities and leading to faster learning compared to conventional model-free RL methods like Deep Q-Network (DQN) in scenarios with low-diversity training data availability. Our results demonstrate that Dyna-PINN has 50% greater sample efficiency than DQN and outperforms rule-based control in terms of thermal discomfort. Due to physics incorporation, the Dyna-PINN implements a more logical and interpretable control policy. It shows consistently good performance compared to all control variants across low-diversity data scenarios, i.e., 6 weeks of building data, and in higher-diversity data regimes, i.e., 6 months of building energy data, demonstrating the value of physics incorporation into the RL training. Additionally, we present two other DDQ-based techniques, RC-DDQ and NN-DDQ, exploring the synergy between neural networks and physical data in intelligent control designs for building energy systems. Rigorous controller testing is performed using the Building Optimization and Testing Framework (BOPTEST), a high-fidelity simulator that closely represents a real building's operation. Through comprehensive comparisons and realistic simulations, our study underscores the effectiveness of incorporating physics-informed approaches into RL-based control strategies, paving the way for more efficient and robust building energy management systems.

Experimental study of performance of building heating system based on HPS and equipped with thermal potential recovery system and heat load prediction

The results of experimental studies of the heating system performance of a building located in the area of temperate continental climate with temperatures in the heating period down to −30 °C are discussed. The studied heating system comprises an air–liquid heat pump, a liquid–liquid heat pump with a ground circuit, and an electric boiler for peak demands.The paper presents the results of the influence of the ground thermal potential recovery system on the liquid–liquid heat pump performance. Also the influence of the used method of heat load prediction on the system efficiency and indoor air temperature stability is shown.Implementation of the thermal potential recovery system allows to increase the average value of the transformation coefficient for the liquid–liquid heat pump from 2.7 to 2.9 during three years of operation.Heat load prediction leads to stable indoor air temperature in the range of 22 ± 1 °C. Also it allows to level out the dependence of indoor temperature fluctuations on outdoor air temperature fluctuations.

THE ROLE OF PROPERTY MANAGEMENT IN PROMOTING ENERGY-EFFICIENT SOLUTIONS FOR RENTALS

Real estate management plays a key role in promoting energy efficient solutions when renting out properties. The purpose of the study is to analyze the impact of management companies on the introduction of energy-efficient technologies to increase the competitiveness of facilities and reduce operating costs. The methodology is based on the analysis of data on the application of modern energy-efficient solutions, including lighting, heating and automation systems in buildings in the Czech Republic. The results showed that the use of such technologies helps to reduce utility costs by 20-40% and increases the attractiveness of facilities for tenants. In conclusion, property management aimed at energy efficiency ensures the achievement of sustainable development and economic benefits for owners and tenants. These measures increase the market value of the properties and extend the lease terms, which strengthens the position in the real estate rental market.

OPTIMIZATION OF HEAT CONSUMPTION IN CENTRAL HEATING SYSTEMS AT COMMERCIAL FACILITIES

Rising energy prices and stricter environmental regulations are exacerbating the problem of inefficient heat consumption in the commercial sector. Central heating systems of office buildings, shopping malls, and industrial complexes are often characterized by excessive thermal energy consumption, which leads to significant economic losses and a negative impact on the natural environment. The purpose of the study is to study the directions and trends of optimization in the field under consideration (taking into account modern technological capabilities, and economic factors). There are disagreements in the professional community about the priority of measures to improve energy efficiency: some experts prefer improving the thermal insulation of buildings, others — the introduction of intelligent control systems, and others — the integration of renewable energy sources. The present study demonstrates that the greatest effect is achieved with a systematic approach combining various initiatives. The conclusion is formulated that in the current conditions and the future, a comprehensive application of modern thermal insulation materials, highly efficient heating equipment, intelligent management mechanisms, and alternative energy sources is required. The article is of interest to engineers-designers of heating systems, energy managers of commercial facilities, specialists in energy efficiency of buildings, and heads of companies interested in optimizing operating costs and improving the environmental friendliness of their real estate.

Environmental, economic, and eco-efficiency assessment of residential heating systems for low-rise buildings

Transitioning from fossil fuels to renewable heating is essential for rapidly reducing greenhouse gas emissions. Besides greenhouse gas emissions, other environmental and economic impacts are crucial for successfully implementing renewable heating systems. This study evaluates 13 residential heating systems' environmental, economic, and eco-efficiency performance for a typical German two-story dwelling. The life cycle assessment method is employed to quantify the environmental impacts. Assuming a sustainable supply of biomass-based fuels, biomass heating systems exhibit the lowest environmental impacts, whereas gas heating systems are associated with high environmental impacts. Among heat pump systems, the water-source heat pump demonstrates the lowest environmental impact. Additionally, integrating a PV system into heat pump systems reduces the environmental impacts across all heat pumps. The evaluation indicates that the air-source heat pump is the most economical system, while the pellet boiler with solar thermal support and the heat pump with ice storage incur the highest costs. However, the cost differences among the heating systems are relatively small, making it challenging to establish a clear ranking based solely on economic evaluation. An eco-efficiency assessment, which combines environmental and economic aspects into a single indicator, reveals that the most eco-efficient systems are the air-source heat pump, both with and without a PV system, and the wood gasifier heating system. In contrast, the ice-storage heat pump and the pellet heating with solar thermal support show the lowest eco-efficiency.

Development of an FDD model for an existing building using transfer learning

Building heating, ventilation, and air conditioning (HVAC) systems are affected by several errors that can cause thermal discomfort to occupants and waste energy in buildings. Therefore, early and accurate Fault Detection and Diagnosis (FDD) is vital for enhancing the system’s efficiency. Data-driven FDD is promising because it is convenient compared to the first-principles-based rule set that demands in-depth expertise. However, to realize data-driven FDD for real-life cases, the data-imbalance problem in FDD must be solved. In this study, the authors suggest a novel approach that generates synthetic data from a building system simulation tool, HVACsim+, using them as a source model to apply transfer learning to a target air handling unit system. Even though from the existing target system only the normal operational data were available, the transfer learning approach was satisfactory, confirming that the proposed method effectively mitigates data imbalance in developing data-driven FDD.

Health implications of housing retrofits: Evidence from a population-wide weatherization program

This study provides the first population-representative quasi-experimental estimates on the impact of housing upgrades on occupant health. We analyze the exceptional period of renovations in East Germany following the German reunification during the 1990s. Triggered by one of the largest governmental loan programs in history, 3.6 million dwellings were renovated, focussing on upgrades to the building insulation, windows and heating systems. Using rich survey data based on the Socio-Economic Panel (SOEP) as well as administrative records of hospital admissions in Germany, we consistently show that housing weatherization upgrades sustainably reduce the demand for health care among the elderly sample of the population.

Analysis of various system designs for adsorption cycle in building heating applications

Buildings are major energy consumers, highlighting the need for efficient thermal energy storage to reduce reliance on non-renewable sources. Adsorption-based systems offer significant energy savings for heating applications. This research compares four critical adsorption-based cycles: adsorption thermal energy storage, adsorption heat transformer, adsorption mass recovery with heating and cooling, and a novel combined cycle. The study uncovers new insights into temperature and pressure control challenges through lumped parameter modeling. These dynamic modeling results advance our understanding and optimization of adsorption systems, enhancing their feasibility and efficiency for building heating. The adsorption mass recovery cycle demonstrates superior energy storage density (289 kW h/m³) compared to the adsorption heat transformer cycle (240 kW h/m³) and the adsorption thermal energy storage cycle (157 kW h/m³). It also has the highest water uptake (0.56 kg/kg), surpassing the other two cycles. Despite its pressure fluctuations and temperature instability challenges, the adsorption mass recovery cycle outperforms the adsorption heat transformer and adsorption thermal energy storage cycles in energy storage density. The novel combined cycle optimizes heat storage and release, achieves the highest energy storage density (302 kW h/m³), and outperforms the individual cycles. The combined cycle's performance was evaluated in a home in South Korea, revealing significant energy savings and proving an effective solution for enhancing energy efficiency in building heating systems. This research addresses a crucial gap and provides a foundation for future advancements in thermal energy storage.

Integrated optimization of the building envelope and the HVAC system in office building retrofitting

Increasing the energy efficiency of existing buildings is the major strategy to reach carbon neutral targets, given that the building sector is a major emitter. In particular, one major part of building energy usage is the building heating, ventilation and air-cooling system, which are highly depending on the thermal performance of building envelope and increase the challenge of selecting optimal packages of energy efficiency measures. This paper thereby presents a method for optimizing the building envelope and heating, ventilation and air-cooling system. The simulation-based NSGA-III approach developed in this paper is based on coupling the dynamic simulation models created in EnergyPlus software with the non-dominated sorting genetic algorithm, as the engine that performs an optimization process. A large domain of energy efficiency packages combined with heating, ventilation and air-cooling systems and building envelope are investigated to minimize energy consumption, retrofit cost and thermal discomfort in indoor environments, which including ideal loads air system, four pipe fan coil system and variable refrigerant flow system, insulation materials and insulation thickness for external walls and roof, different types of external windows, and window-wall ratio. An office building in Chongqing was chosen as a case study to demonstrate the practical implementation of the proposed method. The results show that the four pipe fan coil system was superior in the diversity and performance of the Pareto front. Then, the optimal packages were generated by a synthetic method, which have 58.57 kWh/m2 of energy consumption, 30.76 CNY/m2 of retrofit cost and 40.67 % of the percentage of thermal discomfort hours. The results also indicate that the yearly energy savings rates are 17.30 %, 23.05 % and 21.10 % separately for ideal loads air system, four pipe fan coil system and variable refrigerant flow system after performing optimization. These results highlight the importance and necessity of performing an optimization procedure for existing buildings to select the optimal retrofit measures.

Strategic integration of residential electricity: An optimisation model for solar energy utilisation and carbon reduction

The Solar Combined Cooling, Heating, and Power (S-CCHP) system, distinct from traditional centralised generation, provides clean energy solutions by installing user-side renewable energy capture facilities like solar panels to address the energy crisis and mitigate global warming. Previous research on the design of S-CCHP for buildings has often emphasised self-sufficiency, with less focus on the role of these systems as energy suppliers on the market. However, it is feasible to install scaled-up solar facilities that generate enough power to export to the grid, reducing grid pressure and enhancing the renewable energy mix. This study analyses the optimal design deployment for electricity within the S-CCHP system, based on the Renewable Energy System for Residential Building Heating and Electricity Production (RESHeat) system installed in Limanowa. It aims to optimise owner energy deployment by strategically integrating electricity generation, hybrid storage, and the electricity market to maximise owner benefits. A Life Cycle Assessment is also conducted to explore greenhouse gas emissions across scenarios with different storage facilities and reuse rates. Results show that the optimal deployment of 264 PV panels, each with a rated power of 440 W, generates 105 MWh annually, resulting in the surplus of 90.18 MWh with a selling price of 115 EUR/MWh. Vanadium redox flow batteries offer the highest revenue (4922.01 EUR) with the lowest storage costs, while lithium-ion batteries have the lowest carbon emissions (1.22 t CO2 eq/y). Sensitivity analysis and revenue break-even analysis are further conducted to assess the robustness and financial viability.

Identifying untraced faults associated with high return temperatures from heating systems in buildings connected to district heating networks

The district heating (DH) system is in its transition towards the 4th generation district heating (4GDH), and the high DH return temperatures need to be addressed during the process. In the existing building heating systems, many faults, malfunctions, or sub-optimal operations can lead to high DH return temperatures. However, the field of fault detection and diagnostics (FDD) within heating systems is notably under-researched in contrast to their counterparts in ventilation and air conditioning in building HVAC systems. This divergence can be attributed to several factors, including limited digital integration, a scarcity of data, and the non-obvious nature of faults in heating systems. In this study, we utilized heat cost allocators (HCA) and energy meters to investigate the features and potential impacts of four untraced faults that can lead to high district heating (DH) return temperatures in both space heating and domestic hot water systems in large buildings. We identified component-level faults, including heat exchanger overflow, space heating temperature controller failures, and excessive operating temperatures due to bypass, as well as system-level issues such as non-uniform heat distribution in buildings and its impacts. This exploration provides new, critical insights for advancing FDD research in HVAC and DH systems.

Optimal scheduling of green heating systems in buildings considering economy and exergy efficiency

Green heating in buildings is of great significance to global energy conservation and emission reduction, and the design of optimal scheduling models is the key to achieve cost reduction and efficiency improvement in heating systems. For the building heating system containing multiple heterogeneous energy sources such as solar energy, air energy and electricity, a multi-objective optimal scheduling model is established with the goal of maximizing the exergy efficiency and minimizing the economic cost of the system, taking into account the quality difference of energy in the conversion process. Regarding the nonconvex and nonlinear constraints in the scheduling model, the incremental linearization method and Big-M method are used to linearize the transformation, and obtain the multi-objective mixed-integer linear programming model. Further, the ε-constraint method is used to solve the Pareto frontier of multi-objective optimization and the technique for order preference by similarity to ideal solution (TOPSIS) method is used to make decision. Finally, the simulation study of the model is carried out, and the results show that the proposed multi-objective optimal scheduling can balance the system operation economy and exergy efficiency compared with the belief rule base and evidential reasoning (BRB-ER) method, and the system’s daily economic cost are reduced by 9.66 %, 9.94 % and 17.24 %, respectively, and the system’s average daily coefficient of performance (COP) are improved by 4.66 %, 14.05 % and 13.22 %, respectively, on three typical days, it is verified that the proposed optimal scheduling model has better economy and exergy efficiency. The proposed multi-objective optimal scheduling model introduces exergy efficiency rather than energy efficiency as one of the optimization objectives of the heating system and reasonably solves the optimization model, which can provide a new idea and reference for the multi-objective optimal scheduling of the green heating system in buildings.

Thermo-economic assessments on building heating by a sewage source heat pump coupled with heat storage system

To enhance the economic feasibility of building heating systems, phase change heat storage materials are often utilized to utilize renewable energy and address system peak loads. This article presents an innovative method of integrating a sewage source heat pump with a heat storage device. Upon an industrial building in Xilinhot as a case study, numerical models for the heat accumulator coupled with the energy consumption of buildings are established, taking into account dynamic hourly loads and meteorological conditions. Through a comprehensive analysis, the thermophysical properties of the heat accumulator as well as the economic implications of the multi-energy complementary heating system are investigated. Results demonstrate that the complete melting time for a 95 % filling rate is significantly reduced, 87.11 % shorter than that of pure phase change material, achieving the highest heat storage efficiency. Furthermore, the phase change storage device with a 75 % filling rate had the shortest investment payback period, requiring only 6 years. These findings have significant implications for guiding green renovation projects in building heating systems.

Decarbonization of Heating and Cooling Systems of Buildings Located Nearby Surface Water Sources: Case Study

The study was carried out to evaluate theoretically and in laboratory conditions the capacity of a hybrid heating and cooling system that sustainably uses thermal energy extracted from surface waters in order to decarbonize buildings located near water sources. The novelty of the research consists in the realization of two experimental systems, one for the rapid evaluation of the performance of the water–water heat pump heating system and one for the evaluation of the operating behavior of a cooling system with fan coil units. Starting with the heating and cooling demand, and the climatic and hydrological local characteristics, a hybrid system model for the heating and cooling of the analyzed building was established and implemented. The forecasted energy consumption and CO2 emissions for the operation of the new equipment were compared with the historical values of the old systems with which the building was equipped (thermal energy supply from the district heating and cooling system with an air conditioning unit). Also, the results were extrapolated for forecasting the energy potential of the surface waters. The study highlights a percentage reduction in annual energy consumption of 67.71% and CO2 emissions of 80.13% through the implementation of the hybrid system.

Hydrogen Blending in Natural Gas Grid: Energy, Environmental, and Economic Implications in the Residential Sector

The forthcoming implementation of national policies towards hydrogen blending into the natural gas grid will affect the technical and economic parameters that must be taken into account in the design of building heating systems. This study evaluates the implications of using hydrogen-enriched natural gas (H2NG) blends in condensing boilers and Gas Adsorption Heat Pumps (GAHPs) in a residential building in Rome, Italy. The analysis considers several parameters, including non-renewable primary energy consumption, CO2 emissions, Levelized Cost of Heat (LCOH), and Carbon Abatement Cost (CAC). The results show that a 30% hydrogen blend achieves a primary energy consumption reduction of 12.05% and 11.19% in boilers and GAHPs, respectively. The presence of hydrogen in the mixture exerts a more pronounced influence on the reduction in fossil primary energy and CO2 emissions in condensing boilers, as it enhances combustion efficiency. The GAHP system turns out to be more cost-effective due to its higher efficiency. At current hydrogen costs, the LCOH of both technologies increases as the volume fraction of hydrogen increases. The forthcoming cost reduction in hydrogen will reduce the LCOH and the decarbonization cost for both technologies. At low hydrogen prices, the CAC for boilers is lower than for GAHPs; therefore, replacing boilers with other gas technologies rather than electric heat pumps increases the risk of creating stranded assets. In conclusion, blending hydrogen into the gas grid can be a useful policy to reduce emissions from the overall natural gas consumption during the process of end-use electrification, while stimulating the development of a hydrogen economy.

Thermal performance of solar ground source heat pump system for rural buildings in Chinese cold zone

In response to China's national policy of “achieving carbon peak by 2030 and carbon neutrality by 2060″, and to promote the heating system of rural buildings in China's severe cold zone. Two heating schemes of the GSHP (Ground Source Heat Pump) system and the SGSHP (Solar Ground Source Heat Pump) system are designed and simulated for a single rural residential building in Harbin city. The results present that the outlet temperature of buried pipe in SGSHP system is 13.86 % higher than that in GSHP system, and coefficient of performance (COP) correspondingly increases 9.2 %. There is a better comprehensive performance for the SGSHP system in cold climates. The standard coal consumption of SGSHP system is about 72.35 % less than that of biomass boiler system, showing a greater energy efficiency. Compared to the local conventional biomass boiler system, the dynamic cost payback period of the SGSHP system amounts to 11 years, while yielding a net present value (NPV) of 10,800 CNY throughout the project's life cycle. The emissions of CO2, SO2, and dust are reduced by 2617.13 kg, 19.38 kg, and 14.535 kg respectively. The results indicate a great overall performance of the SGSHP system for residential heating in the cold climate zone. This research offers an energy efficient and eco-friendly alternative for the space heating of Chinese rural buildings in cold climates.

HAPPENING: an efficient cascade heat pump system for multifamily buildings

An innovative hybrid heat pump system is presented as a novel solution for multifamily building heating system retrofitting. This system is very efficient on the one hand thanks to its innovative configuration in cascade, minimum thermal losses and on the other hand, the maximization of local solar energy self-consumption due to decoupling generation and consumption and applying smart control strategies. It is aimed at facilitating retrofitting of existing heating systems in multifamily buildings, enabling an efficient decarbonization. Three variations of the system have been designed, installed, and tested in real buildings across Europe, within the H2020 project “HAPPENING”. The project is now under monitoring phase and the preliminary results are positive, demonstrating the high efficiency of the concept