Heating System Research Articles

Modeling an Electrolyzer in a Graph-Based Framework

We propose a linear electrolyzer model for steady-state load flow analysis of multi-carrier energy networks, where the electrolyzer is capable of producing hydrogen gas and heat. For our electrolyzer model, we show that there are boundary conditions that lead to a well-posed problem. We derive these conditions for two cases, namely with a known and unknown heat efficiency parameter. Furthermore, the derived conditions are validated numerically. Moreover, we investigate the extensibility of our model by including nonlinear models from electricity, gas, and heat. In this setting, we derived boundary conditions based on our previous findings. Due to the involvement of nonlinearity, it is a challenge to prove that the boundary conditions lead to a well-posed problem. Therefore, we simulated the electrolyzer connected with an electricity, gas, and heat system. Additionally, we considered a known and unknown heat efficiency parameter. The numerical results support that the linear electrolyzer model is solvable in a multi-carrier energy network.

Implementation of Sensor Input Setup Assistance Service Using Generative AI for SEMAR IoT Application Server Platform

For rapid deployments of various IoT application systems, we have developed Smart Environmental Monitoring and Analytical in Real-Time (SEMAR) as an integrated server platform. It is equipped with rich functions for collecting, analyzing, and visualizing various data. Unfortunately, the proper configuration of SEMAR with a variety of IoT devices can be complex and challenging for novice users, since it often requires technical expertise. The assistance of Generative AI can be helpful to solve this drawback. In this paper, we present an implementation of a sensor input setup assistance service for SEMAR using prompt engineering techniques and Generative AI. A user needs to define the requirement specifications and environments of the IoT application system for sensor inputs, and give them to the service. Then, the service provides step-by-step guidance on sensor connections, communicating board configurations, network connections, and communication protocols to the user, which can help the user easily set up the configuration to connect the relevant devices to SEMAR. For evaluations, we applied the proposal to the input sensor setup processes of three practical IoT application systems with SEMAR, namely, a smart light, water heater, and room temperature monitoring system. In addition, we applied it to the setup process of an IoT application system for a course for undergraduate students at the Insitut Bisnis dan Teknologi (INSTIKI), Indonesia. The results demonstrate the effectiveness of the proposed service for SEMAR.

Assessment of Particle Candidates for Falling Particle Receiver Applications Through Irradiance and Thermal Cycling

Abstract Falling particle receiver (FPR) systems are a rapidly developing technology for concentrating solar power applications. Solid particles are used as both the heat transfer fluid and system thermal energy storage media. Through the direct irradiation of the solid particles, flux and temperature limitations of tube-bundle receivers can be overcome, leading to higher operating temperatures and energy conversion efficiencies. Candidate particles for FPR systems must be resistant to changes in optical properties during long-term exposure to high temperatures and thermal cycling in highly concentrated solar irradiance. Seven candidate particles—two previously tested particles such as CARBOBEAD HSP 40/70 and CARBOBEAD CP 40/100 and the five novel particles such as CARBOBEAD MAX HD 35, CARBOBEAD Solar HSP, CARBOBEAD Solar CP, CARBOBEAD Solar MAX HD, and WanLi Diamond Black—were tested using simulated solar flux cycling and tube furnace thermal aging. Each particle candidate was exposed for 10,000 cycles (simulating the exposure of a 30-year lifetime of a concentrated solar power plant) using a shutter to attenuate the solar simulator flux. Feedback from a pyrometer temperature measurement of the irradiated particle surface was used to control the maximum temperatures of 775 °C and 975 °C. Particle solar-weighted absorptance and emittance were measured at 2000 cycle intervals. Particle thermal degradation was also studied by heating particles to 800 °C, 900 °C, and 1000 °C for 300 h in a tube furnace purged with bottled unpurified air. Here, particle absorptance and emittance were measured at 100-h intervals. Measurements taken after irradiance cycling and thermal aging were compared to measurements taken from as-received particles. WanLi Diamond Black particles had the highest initial value for solar-weighted absorptance, 96%, but degraded up to 4% in irradiance cycling and 6% in thermal aging. CARBOBEAD HSP 40/70 particles currently in use in the prototype FPR at the National Solar Thermal Test Facility had an initial value of 95% solar absorptance with up to a 1% drop after irradiance cycling and 4% drop after 1000 °C thermal aging.

Design and Heat Transfer Analysis of Graphene-Based Electric Heating Solid Wood Composite Energy Storage Flooring

Due to severe global energy issues and the widespread demand for high-quality winter heating, this study designed a new type of graphene-based electrically heated solid wood composite floor. This flooring maintains the convenience of a traditional floor installation while providing users with a more comfortable living experience. Additionally, the low-temperature heating and temperature regulation system further reduces energy consumption, offering a new perspective for green home living. This paper introduces the overall structure and temperature control system of the graphene-heated solid wood composite flooring. Based on the above reasons, the working mechanism and heat transfer process of the graphene-heated flooring were analyzed, and a mathematical model was established. Furthermore, simulations of flooring with different thicknesses were conducted to determine temperature rise curves and corresponding times. Finally, a comparative experimental verification was conducted on the thermodynamic performance of the solid wood composite graphene flooring. The results showed that in the case of a floor with an 18 mm thickness, the time for the surface layer of the floor to reach 22 °C is 27 min; the time to reach 26 °C is 56 min; and that the time to reach 28 °C is 109 min. The time required to return to 22 °C after the power has been switched off is 25 min. The results also showed that one hour after the power was turned off, the surface temperature of the floor was still above 20 °C. The study shows that the graphene-heated flooring can be used to achieve high-quality heating.

OPTIMIZATION OF PARAMETERS OF SOLAR COLLECTORS CONCENTRATORS FOR GREEN BUILDINGS

The use of solar collectors with solar concentrators in green buildings is an important step in the direction of creating energy-efficient and environmentally friendly buildings. These technologies make it possible to provide a sustainable source of energy, reduce emissions and save resources. Considering the positive aspects of using solar collectors, their implementation in construction can become an important step in the development of sustainable construction and environmental protection. The use of solar collectors with concentrators can significantly reduce the consumption of electricity and other energy sources, which is an important aspect for green buildings. These collectors are able to efficiently collect solar energy and concentrate it for further use in various heating, cooling and power generation systems. Increasing the energy efficiency of green buildings is possible due to the use of solar systems with optimal orientation parameters that use renewable, environmentally friendly solar energy for the energy supply of buildings. An analytical method has been developed to determine the optimal parameters - the angle of inclination of the solar collector reflector to obtain the maximum amount of converted solar energy, taking into account the number of glass layers, their transparency and absorption coefficient depending on the angle of incidence of reflected solar rays, shading by the collector frame, etc. Calculations were made and optimal angles of the reflector were determined for single-layer and double-layer glazing of the collector. The proposed method can be used in the design of green buildings that use solar energy for energy supply.

Multiload Resonant Inverter With Boosting for All‐Metal Domestic Induction Heating System

ABSTRACTInduction heating (IH) systems have gained significant attention because of their high efficiency, rapid heating, versatility, and precise control. Induction cooking (IC) is one of the primary domestic applications of IH technology. Traditional IC systems typically employ single‐frequency inverters optimized for ferromagnetic (FM) material loads. This approach presents limitations when confronted with various cookware materials including nonferromagnetic (NFM) materials. To address the growing demand for multimaterial load IC systems with enhanced performance and flexibility, a multiload resonant inverter integrated with boosting is proposed with a double full‐bridge three‐leg architecture. The proposed system features three independent legs, each operating at a different frequency to power three different material loads. Integrating this topology with boost functionality enhances performance and optimizes energy utilization. Pulse frequency modulation (PFM) and asymmetrical duty cycle (ADC) control techniques are used to control the load powers independently and simultaneously. A detailed analysis of the inverter and its design procedure is presented. A 1.5‐kW hardware prototype is designed, and the experimental results are in good agreement with the simulation results.

Tobacco Heating System: a Scientific Review of the Scientific Literature on Aerosol Composition

Regulation of the concentration of toxic substances derived from tobacco products is carried out to reduce the incidence of deaths and diseases caused by the use of tobacco cigarettes, as well as to decrease attractiveness, addiction, and toxicity. In this context, modified risk tobacco products (MRTPs) have been developed to provide alternative products that have the potential to reduce the risk and harm to the population when compared to smoking conventional cigarettes. One example of an MRTP is the Tobacco Heating System (THS2.2), which, unlike conventional cigarettes, heats the tobacco instead of burning it, producing a significantly reduced amount of harmful and potentially harmful constituents (HPHCs). To review the data on the content of HPHCs in the aerosols and smoke of conventional cigarettes and those of the THS2.2 type, a critical review of scientific publications in this field was conducted from January 2015 to May 2022. The selection of scientific publications from open sources was carried out from the Scopus, Web of Science, Google Scholar, PubMed, MedLine databases, and others. A similar analysis was carried out on the information already available on the websites of Philip Morris International (PMI), Elsevier, Springer, and other relevant web resources that include information on the use of the THS2.2. After conducting a comprehensive analysis of results from both independent and industry-sponsored studies, it was noted that HPHCs are not completely eliminated from the aerosol produced by heated tobacco products (HTPs). However, the levels of these HPHCs from the PMI List of 58 Constituents (PMI-58 list) are consistently lower and significantly reduced when compared to the mainstream smoke emitted by conventional cigarettes. This suggests that while HTPs present reduced emissions of toxicants in comparison, they are not completely free from risks.

Direct Load Control Strategy of Centralized Chiller Plants for Emergency Demand Response: A Field Experiment

As the penetration rate of renewable energy in the power grid increases, the imbalance between power supply and demand has become one of the key issues. Buildings and their heating, ventilation, and air conditioning (HVAC) systems are considered excellent flexible demand response (DR) resources that can reduce peak loads to alleviate operational pressures on the power grid. Centralized chiller plants are regarded as flexible resources with large capacity and rapid adjustability. The direct load control of chiller plants can respond to the power grid within minutes, making them highly suitable for participation in emergency DR. However, existing studies are generally based on simulations and lack experimental research in actual large-scale buildings to demonstrate the effectiveness of this method and provide related lessons learned. This study conducted field experiments on a centralized chiller plant within an industrial building in Guangdong, China. The results indicate that the strategy of shutting down chiller plants is an effective DR measure. It can complete the load reduction process within 15 min, rapidly decreasing the system power by 380~459 kW, with a maximum duration of up to 50 min, without significantly affecting the thermal comfort of indoor occupants. Additionally, the impact of existing control logic on the participation of chiller plants in the DR process is also discussed.

Energy efficiency and economic performance of a low-temperature heating system combining double-layer pipe-embedded wall and ground source heat pump

Reducing heating energy consumption in buildings is a crucial step towards a low-carbon future. The energy efficiency of heat pump heating systems can be improved by reducing the water supply temperature of terminals. However, existing terminals are limited in using lower-temperature hot water and leaves potential for energy savings. Therefore, this study proposes a double-layer pipe-embedded wall heating system coupled to a ground source heat pump. The outer pipes use shallow geothermal energy to reduce envelope load, whereas the inner pipes use water produced by the heat pump to provide heating. Energy, economic, and carbon emission analysis models of the proposed system are developed. A residential heating case study is conducted in Harbin, Shenyang, Beijing, Zhengzhou, and Shanghai to investigate the performance of the proposed system. The results show that the proposed system achieves much lower-temperature heating than the reference floor heating system. The seasonal energy savings of the proposed system in the selected cities are 12%–18%, with a SCOP of 4.0–5.8. The dynamic payback period of the proposed system is 1.6–4.3 years and the CO2 emission intensity is reduced by 1.2–3.2 kg/m2. This study provides an insight into the application of DPEW heating systems.

Modelling district heating demand: A synthetic dataset for two residential neighbourhoods.

The extensive artificial datasets developed in this study capture the energy demands of two districts and, with reasonable constraints, emulate monitoring campaigns typically conducted on-site in inhabited houses. Generated datasets are the following, one 1) representing low-performing building stock from before the deployment of the Energy Performance of Buildings Directive (EPBD) (2006), and the other 2) reflecting high-performing stock constructed after 2006. The buildings in the datasets were simulated representing single-family homes, typical of neighbourhoods in Flanders, Belgium. The datasets were generated using Dymola and the IDEAS package integrated with TEASER. Each simulated house differs in geometry, size, envelope characteristics, occupancy patterns, and installed gas heating systems. Envelope characteristics for older houses were derived from Energy Performance Certificate (EPC) data, and categorized into four construction periods, while newer houses were based on Energy Performance of Buildings (EPB) reports, both evaluated in Flanders. The datasets feature only heavy-weight houses in terraced, semi-detached or detached configurations, modelled as either single- or two-zone buildings, depending on their number of storeys. The simulations incorporate a natural infiltration model and a stochastic occupant behaviour model that sets the temperature requirements and accounts for heat gains from occupants and appliances. Due to the computational effort of large-scale simulations, heating system performance was postprocessed using a data-driven approach assuming gas-fired heating systems. Six heating system configurations were allocated, including condensing and non-condensing boilers, each combined with one of three domestic hot water (DHW) setups: no integrated DHW, direct DHW, and DHW with a storage tank. For all system designs, production efficiency varied with the load ratio. Urban-scale simulations were carried out at 10-minute frequency using weather data for Heverlee, Belgium, from the year 2016. The primary objective of this dataset was to support the development of statistical tools for characterizing the heat transfer coefficient of building envelopes. However, the generated artificial datasets offer a wide range of typically hard-to-measure inputs, making them ideal for evaluating the impact of simulated components on the overall energy balance. While the initial focus was on the behaviour of individual buildings, these datasets are also valuable for urban-scale analyses, particularly in energy planning contexts.

Parametric analysis and new performance correlation of an innovative system for green hydrogen, oxygen, heat, and electricity production: Application in Pau

Parametric analysis and new performance correlation of an innovative system for green hydrogen, oxygen, heat, and electricity production: Application in Pau

A multi-level optimization design and intelligent control framework for fuel cell-based combined heat and power systems

A multi-level optimization design and intelligent control framework for fuel cell-based combined heat and power systems

Heat transfer modeling and system performance assessment of an innovative thermosyphon radiator integrated with air source heat pumps for sustainable heating applications

Heat transfer modeling and system performance assessment of an innovative thermosyphon radiator integrated with air source heat pumps for sustainable heating applications

Energy, Exergy, Economic and Exergoeconomic (4E) Analysis of a High-Temperature Liquid CO2 Energy Storage System: Dual-Stage Thermal Energy Storage for Performance Enhancement

Liquid carbon dioxide energy storage (LCES) system can improve the renewable energy penetration in the grid, but the mismatch between the compression heat and thermal energy storage (TES) system causes considerable irreversible losses. In this paper, a novel high-temperature (300∼400°C) LCES system with a dual-stage TES loop is introduced to enhance the heat transfer and energy storage performance. The proposed high-temperature LCES system is analyzed from the perspectives of energy, exergy, economics and exergoeconomics. Under design conditions, the round-trip efficiency, energy storage density, and levelized cost of electricity of the improved LCES system are 66.68%, 28.57kWh·m-3, and 0.1315$·kWh-1, respectively. The dual-stage TES loop improves the heat recovery factor and round-trip efficiency by 19.10% and 14.59% compared to the basic LCES system. The parametric analysis indicates that the system performance initially improves and then declines as the operating temperature of the low-temperature TES loop increases. The multi-objective optimization results show that the round-trip efficiency and energy storage density of the proposed high-temperature LCES system are at least 7.43% and 62.49% higher than those of low-temperature LCES systems.

How far back shall we peer? Optimal air handling unit control leveraging extensive past observations

Heating, Ventilation, and Air Conditioning (HVAC) systems play a critical role in ensuring occupant comfort in buildings. Traditional Rule-Based Feedback Control (RBFC) systems, while widely deployed for their simplicity, suffer from low adaptability. Recent improvements, such as Model Predictive Control (MPC) methods demand complex mathematical modeling and substantial expert knowledge, creating a high barrier for system design and optimization. Reinforcement Learning (RL) emerges as a promising solution with its adaptability and model-free nature, albeit challenged by sample inefficiency and suboptimal convergence. Given the intrinsic delayed effects from previous actions and prolonged thermal inertia in the HVAC systems, this study introduces an innovative deep RL framework that can leverage historical observations to refine RL agent performance. By incorporating a state-of-the-art (SOTA) Transformer model, we capture the temporal patterns in HVAC data and build a more precise RL training environment. Implemented on high-resolution, real-world HVAC datasets, our framework showed superior performance in both HVAC system modeling and RL control performance. Specifically, compared to the two baseline models—Bidirectional Long Short-Term Memory (Bi-LSTM) and vanilla Transformer, our proposed RL environment model achieved an average of 30.5% and 35.8% prediction accuracy improvement, respectively. Moreover, our optimal past observable RL agent swiftly delivers 35.3% of electricity saving and 54.4% of thermal comfort improvement over traditional RBFC. These results show the effectiveness of the pioneering integration of extensive historical observations for HVAC operation optimization.

Research on supercritical CO2-based filled type U-pipe solar evacuated tubular collector: A thermodynamically parametric optimization and implementation machine learning modeling

Using supercritical CO2 as a working fluid in a heat and power system operating on solar energy is an advantageous approach that achieves higher efficiency, carbon capture, and emissions reduction. Therefore, the present work focused on researching the effectiveness of developing a supercritical CO2-based U-pipe solar evacuated tubular collector (ETC) by a filled layer that includes contributions to thermodynamic parametric optimization and machine learning modeling to forecast the outlet temperature intelligently. Results indicated that the filled type increase the outlet temperature by 24.29 % compared with the conventional type. The evaluation of the optimization research findings shows that an optimal mass flow rate of 8.0 kg/hr achieves a maximum exergy efficiency of 13.70 % to 14.51 %. Furthermore, the results recommended that arranging 13 tubes with a length of 1800 mm is optimal for exergy efficiency within a mass flow rate range of 6.0–12.0 kg/hr. Based on machine learning implementations, Gradient Boosting, Support Vector Machine, and Multi-Layer Perceptron neural networks can intelligently predict with R2|Tout = 1.000, 0.997, and 0.995, respectively. A polynomial-based GMDH/ML with R2|Tout = 0.986 was presented to intelligently forecast the outlet temperature using five input (Tamb,ṁ,ηopt,Ltube,It) parameters.

Impact of working fluid filling ratio on the performance of a micro-channel loop heat pipe based solar PV/T heat and power system

Impact of working fluid filling ratio on the performance of a micro-channel loop heat pipe based solar PV/T heat and power system

Energy, exergy, economic and environmental analysis and optimization of an adiabatic-isothermal compressed air energy storage coupled with methanol decomposition reaction for combined heat, power and hydrogen generation system

Energy, exergy, economic and environmental analysis and optimization of an adiabatic-isothermal compressed air energy storage coupled with methanol decomposition reaction for combined heat, power and hydrogen generation system

Corrigendum to “Comprehensive analysis and optimization of combined cooling heating and power system integrated with solar thermal energy and thermal energy storage” [Energy Conv. Manag. 275 (2022) 116464

Corrigendum to “Comprehensive analysis and optimization of combined cooling heating and power system integrated with solar thermal energy and thermal energy storage” [Energy Conv. Manag. 275 (2022) 116464

Numerical analysis of the effect of baffle length and arrangement on the thermal performance of solar air channels

Improving heat transfer in solar air ducts is crucial to increasing the efficiency of solar heating systems. The addition of baffles is an effective technique for optimizing this heat transfer. This work presents an in-depth analysis of the effect of baffle length and arrangement in an air channel with rectangular baffles to direct and disrupt airflow, thereby increasing the rate of heat transfer. Computational fluid dynamics was employed for the calculations. The Finite volume method was used to discretize the governing equations, and the SIMPLE algorithm was used to the pressure-velocity coupling. A standard k−ε turbulence model based on Reynolds number ranges of 8000≤Re≤30000 has been used to numerically study flow properties and heat transfer. The results show that adapting baffle length plays a crucial role in controlling flow velocity, which directly influences temperature distribution in the system. In addition, the study reveals that periodic arrangement of baffles (Case C) increases maximum velocity values and optimizes flow by increasing fluid acceleration and dynamic pressure. For a Reynolds number of 30,000, periodic arrangements achieve the highest value for TPF, i.e. 3.267. This indicates that periodic baffles create optimized recirculation zones, improving fluid mixing and heat transfer without excessively increasing flow resistance.