Heating System Research Articles

Study on photovoltaic combined air source heat pump heating system under typical meteorological conditions

Abstract This paper proposes a photovoltaic (PV) combined air source heat pump heating system for rural areas in severe cold regions of northern China, where the current clean heating methods have high costs and low efficiency. The paper uses meteonorm8 and TRNSYS software to derive the typical meteorological parameters and simulate the system performance in a guard room in Shenyang city. The paper analyzes the heat pump power consumption, PV cell power generation, and economic and environmental benefits of the system under different outdoor temperatures in the heating season. The results show that the system can meet the heating demand and maintain a comfortable indoor temperature, with an annual cost of 1603 RMB, which is 61.33% lower than a single heat pump system. The system can also reduce the emissions of carbon dioxide, sulfur dioxide, and dust by 2619.43 kg, 10.78 kg, and 6.91 kg per year, respectively, demonstrating its economic feasibility and environmental contribution.

Enhancing Energy Efficiency in a Palestinian Dairy Factory Utilizing RETScreen Expert

This paper delves into the intricacies of optimizing energy utilization within a dairy manufacturing facility situated in Palestine through the utilization of RETScreen Expert. An exhaustive energy audit is undertaken to meticulously scrutinize and comprehend the existing energy landscape within the dairy factory. This investigation is specifically oriented towards the evaluation of seven distinct energy efficiency strategies, encompassing aspects such as lighting enhancements, insulation upgrades, the maintenance of steam traps, mitigation of steam leaks, harnessing heat recovery mechanisms, and the installation of a solar water heating system. The study extends its purview to encompass environmental concerns, encompassing the estimation of CO2 emissions, and conducts a comprehensive assessment of the economic feasibility associated with these proposed measures. The findings of this investigation unequivocally reveal the substantial potential for diminishing energy consumption and curtailing CO2 emissions, alongside the concurrent enhancement of economic viability through the judicious implementation of the aforementioned energy efficiency initiatives. In essence, this scholarly work serves as a valuable resource, shedding light on the advantageous outcomes achieved by the incorporation of energy efficiency measures within industrial frameworks. It underscores the imperative of a holistic approach, where both environmental and economic dimensions are harmoniously considered in the decision-making processes pertaining to energy-related initiatives.

Prototype, Method, and Experiment for Evaluating Usability of Smart Home User Interfaces

Despite the widespread adoption of smart devices and home automation systems, users still face usability challenges. Additionally, evaluating the usability of smart home systems is not straightforward. Our paper focuses on building a Smart Home Prototype, selecting, and evaluating software User Interfaces (UI). We have chosen the smart home heating system as the basis, but the principles are applicable to other applications. To discuss smart home UIs, it is necessary to understand the components, implementation scenarios, configuration, and operation of smart home systems. Therefore, we devote considerable attention to these topics in the paper. Our smart home system utilizes a Raspberry Pi computer, temperature sensors, servo drives, an Android-based smartphone, and other necessary hardware. We installed and configured open-source software and third-party services on the experimental setup. We provided a brief description of each selected software. We used the Home Assistant operating system, its mobile application, voice assistant Alice, and Telegram chatbot. In our study, we described a methodology for evaluating user interfaces in smart homes and conducted an experiment to assess their usability. The experiment results indicated which interface was more user-friendly and identified the drawbacks of each. In conclusion, we discuss UI features that can improve usability and available options for building a smart home based on capabilities.

Reshaping the World with Computer Technologies and Their Impact on the Development of Processes in the Field of Real Estate Trading

Purpose: This study examines artificial intelligence (AI) impact on real estate, highlighting its role in improving processes, enhancing customer experiences, and ensuring competitiveness while prioritising data protection and security. Methodology/Approach: A comprehensive literature review compared AI technologies in real estate, including drones, the Internet of Things (IoT), cloud computing, big data, 3D scanning, wearables, virtual and augmented realities, and robotics. It examines their impact on operations, focusing on AI in Heating, Ventilation and Air Conditioning (HVAC) systems for energy efficiency and comfort. Findings: AI enhances real estate development by optimising operations, transforming customer relationships, and improving energy efficiency and comfort with AI-controlled HVAC systems. Benefits include automated data processing, better decision-making, and optimised marketing strategies. Research Limitation/Implication: AI has great potential, but its implementation is in the early stages, including in real estate. Challenges include data protection, security, costs, and new hardware for HVAC systems. Broader real-case testing is needed. Originality/Value of paper: This paper broadens the perspective on AI's impact on real estate, showing how to implement AI in various processes. It improves performance and transforms customer experiences, setting new standards for property management.

Measures for Achieving Carbon Neutrality in Domestic Wastewater Treatment Plants

Objectives : In modern society, domestic wastewater treatment plants are essential infrastructure. However these facilities are also major sources of significant greenhouse gas emissions. To mitigate the climate crisis and move towards a sustainable society, reducing greenhouse gas emissions from domestic wastewater treatment plants is an urgent task. Achieving this requires the integrated application of technological improvements and institutional measures.Methods : Fundamental strategies for reducing greenhouse gas emissions from domestic wastewater treatment plants include detailed categorization and quantification of emission sources, the implementation of greenhouse gas reduction facilities, and the enforcement of water usage reduction policies. This study uses modeling software to estimate the detailed emissions of greenhouse gases generated during the domestic wastewater treatment process. Additionally, it establishes the baseline treatment process of the domestic wastewater treatment plant and analyzes the greenhouse gas reduction effects of each facility by incorporating technological methods such as anaerobic digesters and combined heat and power (CHP) systems. Furthermore, it evaluates the impact of reducing water usage through water footprint (WF) labeling on greenhouse gas emissions from the domestic wastewater treatment plant as an institutional approach.Results and Discussion : In scenario analysis, the implementation of anaerobic digesters results in a 6.7% reduction in greenhouse gas emissions compared to the baseline, while the addition of CHP systems to anaerobic digestion is predicted to reduce emissions by 29.1%. By integrating CHP systems with anaerobic digesters and applying WF labeling, a reduction of 38.3% in greenhouse gas emissions from the domestic wastewater treatment plant compared to the baseline is anticipated. These results demonstrate the significant role of implementing anaerobic digesters, CHP systems, and WF labeling in achieving the carbon neutrality goal of domestic wastewater treatment plants.Conclusion : The integrated application of technological methods, institutional approaches, and detailed emission calculations through process modeling can be considered crucial for reducing greenhouse gas emissions from domestic wastewater treatment plants.

Comprehensive Performance Analysis of Hybrid Solar Water Heating Systems: Synergizing Photovoltaic and Thermal Technologies

Abstract: Solar water heaters are an efficient and sustainable technology for meeting the growing demand for hot water in residential and commercial applications. This abstract presents a comprehensive overview of the performance evaluation of solar water heater systems through an extensive experimental study. The study aims to assess the effectiveness and efficiency of different solar water heater configurations under varying operating conditions. The experimental investigation involved the measurement and analysis of key performance parameters such as solar collector efficiency, heat transfer efficiency, thermal storage capacity, and overall system efficiency. A range of factors including solar radiation intensity, ambient temperature, water flow rate, and collector tilt angle were systematically varied to examine their impact on system performance. The results of the experimental study demonstrated the significant potential of solar water heaters in providing cost-effective and environmentally friendly hot water solutions. The solar collector efficiency was found to be highly influenced by the solar radiation intensity, with higher levels of solar irradiation leading to increased thermal energy generation. The heat transfer efficiency was optimized by adjusting the water flow rate and collector tilt angle, ensuring efficient transfer of heat from the collector to the water. Furthermore, the thermal storage capacity of the system played a crucial role in maintaining a consistent supply of hot water during periods of low solar radiation or high demand. Overall system efficiency was found to be strongly dependent on the integration of efficient heat exchangers and insulation materials. Based on the experimental findings, recommendations for system design and optimization were formulated, highlighting the importance of proper sizing, selection of suitable materials, and appropriate control strategies. The results also identified areas for future research, such as the integration of advanced heat transfer enhancement techniques and the utilization of hybrid solar water heater systems

Efficiency analysis of induction heating systems with respect to electromagnetic shielding film's properties

Enhancing induction heating efficiency requires precise material selection and optimal structural design, including consideration of electromagnetic shielding materials. This study explores the impact of material properties on high-frequency resistance (Rs), inductance (Ls), and energy consumption. Metal powder-filled composites and ferrites typically exhibit lower relative permeability (μr) compared to nanocrystals, with an increase in μr leading to enhanced Ls, Rs, and heating efficiency. However, nanocrystalline shielding films show a unique trend where heating efficiency initially rises and then declines for multi-layered films, with a critical point at μr = 1500. Magnetic fragmentation induced imperfections in nanocrystalline films disrupt eddy current paths, reducing energy loss and improving heating efficiency as μr decreases. The notion of “relative conductivity (σ')” is introduced to demonstrate that a reduction in the fragmentation extent leads to the expansion of eddy current pathways as μr increases. This augmentation enhances both σ' and the imaginary permeability (μ''), leading to increased eddy current losses that affect overall efficiency. In evaluating energy efficiency for nanocrystals, it is crucial to consider μ', μ'', and σ' in conjunction, as there is a positive correlation between μ'' and σ'. Finite element analysis (FAE) confirms these observations, showing how film properties impact efficiency. Comprehending shielding mechanisms not only optimizes induction heating but also benefits applications such as wireless charging for electric vehicles and mobile communication devices.

Assessing physicochemical characteristics of a shear-thinning polysaccharide mucilage extracted from marshmallow root (Althaea officinalis L.) by an ohmic heating system

Althaea officinalis L. root mucilage holds promise for food industries due to its functional properties. Despite various extraction techniques, ohmic systems remain underexplored for mucilage extraction. This study aimed to compare the efficacy of mucilage extraction using ohmic systems with maceration and investigate their physicochemical properties. The mucilage extraction was carried out utilizing maceration (M), ohmic-assisted extraction (OAE), and ohmic-assisted vacuum extraction (OAVE). Various parameters were evaluated, such as densities and specific energy consumption. The mucilage obtained by OAE had the highest yield (8.9 %). The highest solubility corresponded to the mucilage obtained by the OAE system (85.18 % at 65 °C). OAVE mucilage had 76.16 % swelling and 82.5 g water/g dry sample binding capacity, while OAE mucilage had 19.6 g water/g dry sample binding capacity. The OAVE mucilage oil absorption (12.3 g oil/g dry sample) was almost twice that of the OAE system. Rheological analysis characterized them as a pseudoplastic behavior. DSC thermogram of mucilage samples exhibited a singular endothermic peak (92.05 to 108.3 °C). FTIR analysis highlighted that the primary constituents of mucilage samples predominantly consisted of polysaccharides. This study concluded that ohmic-assisted extraction was the most efficient method for obtaining mucilage. Further research could explore the potential applications of this mucilage.

Output feedback finite‐time boundary control for an unstable heat PDE with spatially varying coefficients

AbstractThis article studies the output feedback finite‐time boundary control for unstable heat systems with the spatially varying coefficient. First, a finite‐time observer with switched gains under a state‐dependent switching law is designed in order to estimate the states of the system in a finite‐time only exerting one displacement boundary measurement. Next, an observer‐based linear finite‐time control is planned. Namely, a linear switched control under a state‐dependent switching law is proposed to vanish every solution of an unstable heat partial differential equation with spatially varying coefficients in a finite time. We also present explicit forms for the proposed observer gains and output feedback finite‐time controller. Finally, some numerical simulations are provided to confirm the theoretical results.

Experimental study and numerical simulation of concrete pavement electrical heating for snow melting

Road snow accumulation can lead to severe traffic delays, and commonly used deicing agents may pose potential environmental risks. Electrically heated concrete pavement systems utilizing heating pipe technology offer a safe and environmentally sustainable alternative. The snow-free ratio was frequently used as an evaluation index to evaluate the snow-melting performance in road infrastructure. However, the unique wavy temperature distribution during the snow-melting process of the heating system results in discontinuous melting, making the existing snow-free ratio inadequate for accurately assessing its performance and effectively guiding the operational strategy of the heating system. Therefore, this study analyzed the special temperature distribution and proposed a new calculation method for snow-free ratio based on the average temperature and the temperature non-uniformity coefficient of the pavement surface. First, the effects of factors such as heating pipe spacing, embedded depth, heating power, and wind velocity on average temperature and the temperature non-uniformity coefficient were analyzed using finite element simulation. Prediction models for average temperature and the temperature non-uniformity coefficient were then established and validated using the response surface method and experiments. Subsequently, using average temperature and the temperature non-uniformity coefficient as intermediate variables, a new functional relationship between the snow-free ratio and the four factors was established, allowing for satisfactory snow-melting performance to be achieved by adjusting the relevant factors of the heating system. The results show that the error rate between the proposed new calculation method and simulation results is only 4.44 %. Moreover, it was concluded that adjusting spacing and heating power is the most effective strategy for heating systems to achieve optimal snow-melting performance.

A multi-objective energy management optimization for a hybrid electric bus covering an urban route

The development of electrified vehicles is a promising step toward energy savings, emissions reduction, environmental protection, and more sustainable economic growth. In the case of hybrid electric vehicles (HEVs), the energy management strategy (EMS) is essential for their efficiency and energy consumption. Typically, EMS employs rule-based strategies calibrated to general driving conditions. So, this paper proposes to calibrate the EMS of an urban hybrid electric bus that covers a particular route by taking advantage of past driving information. The EMS computes the percentage of the vehicle power demand that must be supplied by each of the sources (fuel and battery) and also controls the heating, ventilating and air conditioning (HVAC) system to achieve cabin thermal comfort. The proposed approach is based on employing an optimal solution by dynamic programing in a previous loop covered by the bus in the considered route. Then, the cost-to-go matrix is stored and used in the following trips by applying the one-step look-ahead rollout, taking profit from the similarities of the loops in the route. To compare and evaluate the performance of the proposed algorithm, a benchmark was carried out by employing the widespread equivalent consumption minimization strategy (ECMS) approach, combined with rule-based strategies in the HVAC control system. Finally, the pareto front presents the trade-off between cabin temperature control performance and total fuel consumption, allowing to compare and evaluate the different EMS calibrations.

Cascaded Heteroporous Nanocomposites for Thermo-Adaptive Passive Radiation Cooling.

Passive radiative cooling is a promising technology for heat dissipation that does not consume energy. However, current radiative cooling materials can only exhibit subambient cooling under atmospheric conditions and struggle to process specific heat accumulation. Thus, a passive thermal regulation mechanism adapted to wide-temperature-range applications is required to match device heating systems. Herein, a heteroporous nanocomposite film (HENF) with thermo-adaptive radiation cooling performance is reported. Compared to conventional porous cooling films with limited scattering efficiencies, the HENFs with multistage scattering have a strong emissivity of 96.5% (8-13µm) and a high reflectivity of 97.3% (0.3-2.5µm), resulting in an ultrahigh cooling power of 114Wm-2. In such HENFs, theoretical analyses have confirmed the spectrum management superiority of the heteroporous unit in terms of the scattering efficiency strength, with their cascading effect enhancing the overall film-cooling efficiency. The high mechanical performance, phase-transition features, and environmental adaptive properties of HENFs are also exhibited. Importantly, HENFs synergistically couple thermal dissipation and absorption to effectively process heat accumulation and counteract thermal shock in heating devices. It is anticipated that thermo-adaptive HENFs will act as a promising platform for device surface thermal regulation over a wide temperature range.

Effectiveness of Air Filtration in Reducing PM2.5 Exposures at a School in a Community Heavily Impacted by Air Pollution

Reducing children’s exposure to air pollution is a priority among California communities heavily impacted by air pollution exposures. We conducted an observational air quality study at a school to investigate the effectiveness of improved Heating, Ventilation, and Cooling (HVAC) system filters and portable air cleaners (PACs) in reducing children’s exposure to fine particulate matter (PM2.5) under real-world classroom conditions. This study included five classrooms, three of which had PACs. Halfway through the study period, high-efficiency HVAC filters were installed in all five classrooms. Continuous measurements of outdoor and in-classroom PM2.5 concentrations were used to evaluate filtration effectiveness. The air filtration strategies, alone and in combination, demonstrated 14–56% reductions in indoor PM2.5 concentrations compared to outdoor levels. There were significant improvements in filtration resulting from HVAC filter upgrades in the two classrooms without PACs (11% and 22% improvement, p < 0.001). Upgrading HVAC filters in classrooms with PACs did not significantly improve filtration effectiveness, suggesting that utilizing both strategies simultaneously may not meaningfully improve air quality under these circumstances. CO2 data, as a proxy for ventilation, helped demonstrate that the observed filtration effectiveness was likely impacted by the variable HVAC system use and open doors.

4E assessment of pyramid distiller performance utilizing V-corrugated wick material and TiO2 nanoparticles with hybrid solar heating

This study aims to increase freshwater productivity and thermal performance while improving the economic determinant of the traditional square pyramid distiller. The study was conducted on four modified pyramid distillation systems and their impact on 4E (Energy, Exergy, Economic, and Environmental). The V-corrugated wick material was combined with the water basin in the first configuration (AHPSS-1). The second system uses the same components but integrates a Solar Air Heater (SAH) to raise the water temperature (AHPSS-2). In the third proposed system, a hybrid solar heating system was used by combining a PV-powered electric heater with the previous system (AHPSS-3). The fourth configuration was similar to the third but with the addition of titanium oxide nanoparticles in the water to augment heat transfer performance (AHPSS-4). Thermal analysis of the proposed systems was performed to evaluate their thermal performance in various aspects of energy and exergy efficiency relative to the Conventional Pyramid Distiller (CPSS). In addition, an economic and environmental analysis was conducted for each case of the proposed systems. The outcomes showed an apparent enhancement in thermal and economic analyses versus the CPSS for the four proposed systems. Moreover, there was an improvement in productivity by 27.6, 102.5, 147.8 and 161.5 % for AHPSS-1, AHPSS-2, AHPSS-3, and AHPSS-4 severally. Consequently, the performance of the fourth proposed system was optimum compared to other cases, where the total freshwater yield of the conventional and novel pyramid solar distiller reached 3.9 and 10.2 L/m2. In addition, the daily thermal efficiency and the cost of one liter reached 69.8% and 0.011 USD. Furthermore, the annual CO2 emissions for the modified configuration were estimated at 9.44 and 19.75 tons/year versus 7.48 tons/year for CPSS. Also, the enviroeconomic parameters ranged from 136.81 to 286.35 USD/year.

Investigation of the indoor air temperature in a civilian building after an emergency shutdown of the heating system

Investigation of the indoor air temperature in a civilian building after an emergency shutdown of the heating system

Enhancing Ultra Low Temperature District Heating Systems with Neighborhood-Scale Heat Pumps and Triple-Pipe Distribution: A Techno-Economic Analysis

Ultra-Low Temperature District Heating (ULTDH) systems are advanced District Heating (DH) systems enabling the efficient utilization of low-temperature heat sources for heating systems. A significant challenge in ULTDH systems is the economic inefficiency associated with use of booster Heat Pump (HP) in buildings to achieve the desired Domestic Hot Water (DHW) temperature. To address this issue, this study proposes an innovative ULTDH system incorporating neighborhood-scale water-source booster HPs and distribution triple-pipes. Triple pipe’s dual supply line capabilities facilitate the neighborhood-scale water-source booster HPs to be brought out at the neighborhood scale, demonstrating an intelligent approach. This approach reduces the capital investment and enhances the Coefficient of Performance (COP) by utilizing supply line of DH system as the heat source. A comprehensive case study is conducted to demonstrate the superior techno-economic performance of the proposed ULTDH system compared to Low Temperature District Heating (LTDH) as the benchmark solution. All components of both systems are sized by determining the DHW and Space Heating (SH) demands for each neighborhood. Thermodynamic analysis is conducted at a 1-minute time resolution for an entire year. Six different heat production scenarios are developed to determine the Levelized Cost of Heat (LCOH). The results indicate that while the energy performance of the ULTDH surpasses LTDH, the rise in electricity prices favors the ULTDH system.

Acoustic optimization of a tee via a Helmholtz resonant cavity and noise prediction via a genetic algorithm coupled with the grey model

As a key local component in heating, ventilation and air conditioning (HVAC) systems, the acoustic characteristics of the tee largely determine the indoor acoustic environment quality. The aim of this study was to determine the impact of the Helmholtz resonant cavity (HRC) on the tee noise and sound transmission loss (STL). The noise was predicted using the Ffowcs Williams-Hawkings (FW-H) equation and large eddy simulation (LES), and an analysis was conducted on four design variables: the cavity width, cavity height, outlet flow ratio, and hole width. The results indicated that increasing the hole width had a positive effect on reducing the noise of the tee. HRC could result in a tee peak noise attenuation up to 34.81 dB. In addition, based on grey model (GM) and genetic algorithm (GA) theory, the noise of the Helmholtz resonant tee (HRT) was predicted, and a noise prediction formula for resonant cavity structure paraments was derived. This study provides a new perspective for optimizing the STL of the tee and a simplified prediction method for low-noise tee design.

Heat transfer and system performance of a novel solar ground-source heat-pump system with borehole heat exchangers using a combined parallel and series connection

Heat transfer and system performance of a novel solar ground-source heat-pump system with borehole heat exchangers using a combined parallel and series connection

A Deep Reinforcement Learning-Based Method for Dynamic Quality of Service aware Energy and Occupant Comfort Management in Intelligent Buildings

Buildings are responsible for 30% oof the world’s energy consumption, about half of which is consumed by Heating, Ventilation, and Air Conditioning (HVAC) systems. Intelligent control of these can significantly reduce global energy consumption. However, these systems are also one the most important means of providing comfort to occupants within buildings. These two control objectives may conflict with each other, which means that reducing the energy consumption of the HVAC systems may lead to dissatisfaction among buildings’ occupants. Thus, in most cases, to handle the trade-off, weights are assigned to these objectives which indicate their importance. The priority of these goals may change throughout the operation, meaning that the value of assigned weights must change. To solve this problem, existing methods needed to be retrained every time that the weights changed, which is time-consuming and costly. Thus, an algorithm that can adapt to weight changes in operation time is needed. In this research, a dynamic multi-objective deep reinforcement learning algorithm is introduced to control the power of the HVAC system. Since it is needed to control the continuous power of the HVAC system, a Deep Deterministic Policy Gradient (DDPG) algorithm empowered by Tunable Training, is proposed which can adapt to changes of objectives weights. The controller can adapt to changes in the importance of objectives during operation and does not need to be retrained. The proposed method is compared with a dynamic multi-objective Deep Q-Network (DQN) Algorithm, which is used for discrete control, in a smart home. The results show that the cost of energy in the proposed method is up to 14% lower than the DML-DQN algorithm.

Bi-level optimal configuration of renewable electricity based heating in substations of district heating systems

District heating systems (DHS) are the largest energy consumers in the building energy sector. Substituting electricity in DHS is a pivotal way to achieve its low-carbon development. Existing studies configure the electric heating equipment on the heat source or load side, ignoring the influence of the thermal characteristics of the heat network on the system design and scheduling operation. The impact of the configuration location of the electric heating equipment on system performance is also not emphasized. This paper proposes a new renewable electricity based heating mode in substations of DHS. A bi-level optimal configuration model based on thermal-electricity synergy is proposed to determine the ideal placement, capacity, and operational planning for these heating equipment. The results show that the proposed model reduces operational and environmental benefit costs by 13.31 % and 5.35 % during the heating season. Additionally, it lowers the annualized cost by 6.24 % and curtails the annual discarded wind/photovoltaic power output by 88.76 % through a bi-level optimal configuration model. This method realizes the integration of electrical and thermal energy, enhancing renewable energy consumption while concurrently diminishing operating expenses. Consequently, the heating system achieves superior economic and environmental performance.