Indoor Comfort Temperature Research Articles

Investigating the gender differences in indoor thermal comfort perception for summer and winter seasons and comparison of comfort temperature prediction methods

Formulation of indoor thermal comfort guidelines is challenging task considering the fact that these guidelines are supposed to address both, the expectations of the building occupants' regarding indoor thermal comfort, and optimize building energy use, under aggravating conditions of outdoor climate and availability and price volatility of energy. Therefore, a field survey was conducted to assess indoor thermal comfort in two female and three male dormitory buildings. Afterwards, a comparative analysis of three comfort temperature prediction models (linear, cubic and logistic) was conducted. In total, 971 survey forms were collected during the two seasons (summer and winter). Two-third of the data was used to develop the models, while remaining one-third was used to test the accuracies. Although thermal sensation votes of both genders were statistically different, no statistical difference in indoor comfort temperature between the two genders was observed. Comfort temperatures were calculated as 26.4 °C and 27.8 °C during summer and 22.7 °C and 22.4 °C during winters for female and male occupants respectively, using liner regression method. Following the Griffth's method mean operative comfort temperatures were calculated as 26.8 ± 1.5 °C and 27.6 ± 1.7 °C during summer and 22.7 ± 2.3 °C and 22.3 ± 2.0 °C during winter for female and male occupants respectively. Percentage accuracies of three prediction methods under study showed better performance of logistic regression.

Heat flexibility evaluation and multi-objective optimized control of a low-energy building with district heating

Along with the increasing application of the renewable energy in the energy systems, the future energy system will be more stochastic and fluctuated. Therefore, it is of great importance to effectively coordinate the energy supply and demand side considering their different dynamic characteristics. This study analyzes the impact of the integrated energy flexibility from the building mass and the storage tank on the heating system operation for a low-energy building connected to district heating (DH). According to the actual room occupancy and dynamic heat price, the strategy to unlock the energy flexibility is developed and optimized. The detailed thermal performance of the system is simulated by Modelica models. Compared to the reference case, the integrated energy flexibility is helpful to make better use of the low-price heat. Moreover, a variety of quantification indices were developed to evaluate the flexibility and rebound effect. The results show that the fully charged thermal mass of the low-energy building can help maintain the comfort indoor temperature for up to 43 h. Combined with the storage tank, the heat flexibility potential of the case building reaches 78 kWh and saves 1.1 DKK of the daily heat cost with the optimized heating strategy compared to the reference scenario. Moreover, the flexibility factor is improved by shifting the peak heat load to the low-price period.

Towards comfortable and cost-effective indoor temperature management in smart homes: A deep reinforcement learning method combined with future information

The extension of in-home time has boosted people's increase demand for comfortable indoor temperatures. This paper aims to propose a smart home-based temperature control framework based on deep learning and reinforcement learning to automatically control indoor temperature. The heat pump power and the ventilation system volume could be adjusted by the proposed framework to minimize costs while maintaining indoor comfort. The uncertainty of future information and the requirement for continuous control make it challenging to build an intelligent temperature control system. Simultaneously, the human body is sensitive to different temperatures. Therefore, the selection of appropriate evaluation criteria for people’s thermal comfort is essential. To address this problem, the Predicted Mean Vote (PMV) criterion is applied to scientifically evaluate human thermal comfort. The indoor temperature control problem is transformed into a Markov decision process. A deep learning framework (Proximal Policy Optimization PPO) based on continuous control actions is proposed to solve this problem. Combined with the deep learning method Long Short-Term Memory (LSTM), future state information is applied to improve the control stability. The proposed framework performs well under different conditions in summer and winter. The proposed framework performs well under different conditions in summer and winter. It is compared by the discrete action control method Deep Q Network and the PPO algorithm, which does not contain future state information. As a result, the proposed framework achieves 24.29% and 23.63% cost savings in winter and summer, respectively.

A New Type of Air Conditioning System Based on Finned Ceiling Radiant Coupled with Independent Fresh Air and Its Thermal Comfort Experimental Study.

The traditional radiation air conditioning system has some problems, such as easy condensation, insufficient refrigeration capacity, complex structure, and control system. Therefore, this study proposes a new type of finned metal radiant plate with large heat flow per unit area, sufficient cooling capacity, and simplified heat exchange system, in order to realize large temperature difference between cooling and heating. The temperature field uniformity and thermal comfort test of a novel type of finned ceiling radiant panel and independent fresh air linked air conditioning system under summer cooling and winter heating circumstances are accomplished through artificially generated climate environments. The study's findings demonstrate that in the radiation and fresh air modes, the maximum interior temperature differential under cooling conditions does not rise over 2.1°C. The maximum temperature differential in the space at any one moment in the radiation and fresh air modes cannot be greater than 3°C when heating conditions are present. The fresh air's cooling and dehumidifying effects are clear. The dehumidification efficiency may reach 50%, and the moisture content ranges from 5.48 to 9.63 g/kg. With PMV ranging from −0.34 to 0.54, the enhanced air conditioning system in this research provides exceptionally good thermal comfort. Additionally, the finned radiant panel's installation area occupies just 14% of the ceiling, which is sufficient to fulfill the room's cooling and heating load needs as well as provide high thermal comfort and consistent indoor temperature. The theoretical investigation and practical implementation of the direct expansion radiant air conditioning system are both strongly supported by this research.

Effects of quilts on comfortable indoor temperatures and human thermal responses during sleep.

Quilts play a vital role in the thermal comfort of sleeping people. This study aims to investigate the comfortable indoor temperatures and thermal responses when people sleep in different quilts. The experiment tested three kinds of quilts (down, silk, and polyester), and each kind of quilt involved six filling weights. Sixteen participants (eight males and eight females) conducted whole-night sleeping trials to acquire skin temperatures, bedding temperatures, and thermal perceptual responses. The lower and upper limits of air temperatures ( and ) for comfortable sleeping were obtained. The results indicated that thermal sensation votes were in the range from 0.1 (close to "neutral") to 1.3 (close to "slightly warm") when participants felt comfortable and preferred "no change" in thermal preference. The corresponding comfortable mean skin and bedding temperatures were 34.6 ~ 35.2°C and 31.2 ~ 32.7°C, respectively. and had good linear correlations with bedding insulations. For the same bedding insulation, the and were highest for using silk quilts, followed by down and polyester quilts. The comfort ranges of air temperatures and quilt insulations were finally determined. The findings may benefit understanding the thermal requirement of quilts and help people select and design quilts to achieve thermal comfort.

Experimental and Co-Simulation Performance Evaluation of an Earth-to-Air Heat Exchanger System Integrated into a Smart Building

Building models and their connected subsystems are often simulated as standalone entities. However, in order to monitor a system′s reactions to changing parameters and to assess its energy efficiency, it must be exposed to the actual dynamic context of the building under study. Hence, frameworks assessing co-operative simulation of buildings and their subsystems should be used. In this study, the Building Control Virtual Test Bed (BCVTB) framework was used for co-simulation of a small-scale building (EEBLab) connected to an Earth-to-air heat exchanger (EAHE). The EnergyPlus tool was used to simulate the indoor air temperature variations within the EEBLab, and MATLAB was used to model the EAHE system and to calculate its performance based on various parameters. The HOLSYS internet of things platform was deployed to monitor and collect the experimental data from the sensors to validate the simulations. A favorable agreement between the experimental and simulation results was obtained, showing the contribution of the small-scale EAHE system in maintaining a comfortable indoor temperature range inside EEBLab. Moreover, it demonstrated the effectiveness and accuracy of the proposed approach for integrated building co-simulation and performance evaluation.

Binary/Ternary MOF Nanocomposites for Multi‐Environment Indoor Atmospheric Water Harvesting

AbstractIntroducing atmospheric water harvesting (AWH), beyond the arid atmosphere, under comfortable indoor humidity and temperature regime has its urgency in terms of commercialization and addressing the worldwide freshwater crisis. Herein, the synthesis and characterization of a series of binary (aminopropyl functionalized magnesium phyllosilicate or aminoclay, and CuBTC) and ternary (aminoclay, graphene oxide, and CuBTC) MOF nanocomposites and their water storage and harvesting properties from the indoor atmosphere are demonstrated. The nanocomposites show enhanced hydrothermal stability—39.5% increase in water uptake capacity (with respect to bulk CuBTC) with 67.2% of utmost water harvesting efficiency by blending aminoclay and graphene‐oxide with CuBTC MOF. The study further extrapolates the water collection dynamics by varying ambient humidity, release temperature and on‐demand sorption/desorption cycle under the ordinary indoor condition without any solar irradiation. The ternary nanocomposite enables 0.431 gg−1 of water at 90% relative humidity with a maximum value of 0.445 gg−1 indoor water collections per day.

Optimal positioning of phase change material and insulation through numerical investigations to reduce cooling loads in office buildings

Thermal comfort is inevitable in maintaining the healthy mood of the building occupants and hence increases their productivity. The main objective of this work is to identify the optimal positioning of Phase Change Material (PCM)/insulation techniques with respect to the building envelopes to enhance the thermal performance, thereby recommending effective techniques to reduce the cooling load demand of an office building located under different climates in India. Building models by integrating PCM and insulation layers at various locations of the building envelopes were developed using DesignBuilder software and investigated for summer conditions. The results were compared with that of the basic building. It is concluded that the buildings integrated with PCM or insulation at the outer walls exhibited comfortable indoor temperatures than those integrated at the innermost walls, irrespective of the building location. The selection of PCM and insulation for any location is to be made depending upon the average external temperatures of that specific location for effective and enhanced performance. Based upon the average external temperatures, appropriate techniques were recommended for buildings in different climates. Compared to basic building, the recommended buildings yielded a cooling load reduction of 64%, 61%, 57%, 63%, and 58/59% for Bangalore, Delhi, Jodhpur, Pune, and Guwahati.

Turing Pattern‐Inspired Highly Transparent Wood for Multifunctional Smart Glass with Superior Thermal Management and UV‐Blocking Ability

AbstractTransparent wood for smart glass can decrease indoor energy consumption, while simultaneously offering a comfortable indoor temperature and facilitating effective light harvesting. However, high transparency and ultraviolet (UV)‐blocking ability are mutually exclusive in wood‐based materials due to the presence of lignin. Herein, a Turing pattern‐inspired highly transparent wood (TP‐TW) is fabricated via infiltrating the thermal management materials doped‐epoxy (TMM‐epoxy) into the delignified wood with a Turing pattern. Afterward, the Turing pattern possesses outstanding optical properties (high visible transmittance of ≈76% and low UV transmittance of ≈15%). Moreover, TP‐TW can reduce adverse effects caused by indoor temperature fluctuation and outdoor sunlight, demonstrating high latent heat (25.30 J g−1) and low near‐infrared transmittance. Compared with glass, TP‐TW exhibits a low thermal conductivity of 0.21 W m−1 K−1 and excellent shock‐resistant characteristics. Taken together, these results indicate that TP‐TW is an attractive material for smart glass applications.

Regulation capacity evaluation of large-scale residential air conditioners for improving flexibility of urban power systems

The residential air conditioners (RACs) are increasing rapidly in urban power systems and have been widely considered as good regulation resources for improving the system flexibility and resiliency. However, in practical power systems, it is difficult to comprehensively acquire millions of RACs’ operating data and buildings’ thermal data, which makes the available regulation capacity of RACs tricky to evaluate. To address this issue, this paper proposes a Gaussian Mixture Model (GMM)-based evaluation method by utilizing partial easily observable data. First, a control framework of large-scale RACs is developed to provide regulation services for the power system. Based on the thermal–electrical models of RACs and buildings, a quantification method of the available regulation capacities is proposed under the premise of guaranteeing all the users’ comfortable indoor temperatures. Considering the practical condition of insufficient data acquisition of large-scale heterogeneous RACs, a GMM-based evaluation method is designed to calculate the probability of semi-info RACs’ expected regulation capacities by sampling a small portion of full-info RACs’ characteristics. Moreover, the Expectation Maximization Algorithm and the Bayesian Information Criterion are employed to optimize the multi-dimensional parameters and the component number of the GMM, which significantly improve the evaluation accuracy with lower complexity. The proposed models and methods are verified in a demonstration project on demand response in China.

Processing wood into a phase change material with high solar-thermal conversion efficiency by introducing stable polyethylene glycol-based energy storage polymer

Wood is widely used in the field of building materials as a green and renewable natural porous material. With the continuous increase of global carbon dioxide emissions and increasingly serious environmental problems, improving the energy storage performance of wood is conducive to reduce carbon dioxide and regulate the temperature of the living environment. In this work, a composite phase change material is prepared by introducing stable polyethylene glycol-based energy storage polymer (PGMA) into the porous structure of delignified wood by high temperature immersion method. The wood structure has a greater influence on the crystallinity of PGMA and the modifier is widely distributed inside the lumen and also the cell wall, with crystallinity of 90% PGMA-Wood up to 8.97% and it exhibits good dimensional stability at high temperature. The thermal conductivity of 90% PGMA-Wood is increased to 0.32W/m·K, which reaches 190% higher than that of original wood for the lattice heat transfer replaces phonon heat transfer. The phase change temperature of 90% PGMA-Wood meets the comfortable indoor temperature for human with the melting enthalpy and solidification enthalpy are 25.12 J/g and 31.59 J/g, respectively. The simulated sunlight experiment shows that under the same lighting conditions, the indoor temperature of the house model made by 90% PGMA-Wood is 3 °C higher than that of the house made of original wood, which also has stronger thermal insulation performance at low temperature. All above indicates thatPGMA-Wood have great potential applications in the field of solar-thermal energy conversion and storage as building insulation board and agricultural greenhouses.

Investigation of the effect of the envelope on building thermal storage performance under model predictive control by dynamic pricing

Dynamic pricing is designed for the load shaping to help match the amount of the energy demand to the energy supply capacity. Since the buildings’ characteristics influence the performance of the energy shifting, renovation of the building towards a higher energy flexibility is worth investigating. This study evaluated the effect of the envelope on building thermal storage performance. A model predictive control (MPC) was developed to achieve a multi-objective control i.e., indoor comfort temperature and minimise the total energy cost. MPC automatically triggered the energy storage during the low price periods and used the stored energy during the high price periods. The results confirmed the ability of MPC on peak demand reduction up to 45% electricity cost. Besides, the results also demonstrated the ability of heavyweight thermal mass in terms of reducing energy consumption and shifting a greater high price energy to the low price times. Therefore, adding insulation layers into the lightweight thermal mass is highly recommended, especially for the places experiencing the significant mismatch between the demand and supply during daily peaks or the areas scheduling a large amount of intermittent renewable energy source in the energy production.

Modeling and control of central air conditionings for providing regulation services for power systems

The increasing renewable energies bring more generation fluctuations to power systems, which puts forward a higher requirement on regulation services for maintaining the system balance. Existing traditional generating units probably cannot provide sufficient regulation services to solve this challenge. With the progress of information and communication technologies, it is possible to control demand-side flexible loads to provide regulation services. Among various flexible loads, central air conditionings (CACs) have huge regulation potential, because CACs account for about 40% of the total energy consumption in buildings. However, the operation of CACs is a complicated dynamic process with multiple subsystems and independent control loops. It is difficult to accurately regulate CACs to reach the required regulation services within the comfortable indoor temperature. To address this issue, this paper focuses on the quantitative assessment and two-layer coordinated controls of CACs to provide regulation services for the power system. Firstly, the thermal-electrical model of the CAC is established to describe the dynamic operation process of subsystems’ characteristics. On this basis, a quantitative assessment method of CAC’s regulation services is proposed by discretizing the thermal-electrical operation characteristics. Then, to aggregate multiple CACs to provide significant regulation capacities, an adaptive allocation method is proposed to satisfy the power system’s regulation requirement based on different CACs’ available regulation potential. Furthermore, an online distribution control method is developed to regulate each individual CAC’s cooling capacity for guaranteeing the regulation accuracy and different occupants’ comfortable temperatures. The effectiveness of the proposed models and methods is illustrated by numerical studies.

Simulation of the Regulation Law of Buildings With Unbalanced Heating by Using the Method of Partition Intermittent Heating

Abstract Central continuous heating is widely used in China. Due to the large heating area, the indoor temperatures of the buildings with the same heat source are quite different, which affects comfort and wastes energy. This paper proposes a subsection intermittent heating method, that is, an intermittent heating method is used for overheated buildings. During the period, when the overheated buildings stop heating, the hot water originally supplied to the overheated buildings is supplied to the underheated buildings. We investigated the indoor temperatures of some actual buildings in Daqing city. Accordingly, a comfortable indoor temperature range was determined. The indoor temperature and heating energy consumption of overheated and underheated buildings with zoned intermittent heating were simulated using EnergyPlus. The results show that the interval time has important effects on the indoor temperature and energy consumption of overheated buildings. The most ideal partitioned intermittent heating regulation method is to stop heating (at 5 o’clock) for 3 h and then resume heating for 5 h. When the area ratios of overheated buildings and underheated buildings are 1:1, 2:1, and 3:1, the average indoor temperatures of underheated buildings can be increased from 16 °C to 17.65 °C, 19.05 °C, and 21.02 °C, respectively. The hot water temperature and insulation thickness have significant effects on the indoor temperature of underheated buildings.

The impact of building occupant habits on heating energy consumption: a case study

Abstract The effort to reduce the consumption generated by the use of buildings is one of the important objectives of today’s global society, involving authorities that regulate the energy performance of buildings, manufacturers of materials, specialists involved in the design and last but not least the occupants of buildings. The habits of the occupants of buildings regarding the indoor comfort temperature have a direct influence on the amount of energy consumed. The paper aims to highlight whether the results expected by applying the values recommended in the regulations are in line with the occupant’s habits. Based on a case study, the energy requirement for heating was assessed using different indoor temperatures, which were established in relation to the temperatures monitored in situ. The inside temperature values were monitored in three buildings, located in the third climatic zone of Romania. The article presents the results of the case study, emphasizing that indoor temperature control and monitoring are of high importance in the desired expectations for energy performance of buildings, to meet the sustainability objectives. Knowing the mutual influence between energy consumption and thermal comfort demands, building designers can find solutions to achieve energy conservation goals.

Numerical Study on the Suitability of Passive Solar Heating Technology Based on Differentiated Thermal Comfort Demand

Indoor thermal comfort and passive solar heating technologies have been extensively studied. However, few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfort demands. This work took the rural dwellings in Northwest China as the research object. First, the current indoor and outdoor thermal environment in winter and the mechanism of residents’ differentiated demand for indoor thermal comfort were obtained through tests, questionnaires, and statistical analysis. Second, a comprehensive passive optimized design of existing buildings was conducted, and the validity of the optimized combination scheme was explored using DesignBuilder software. Finally, the suitability of passive solar heating technology for each region in Northwest China was analyzed based on residents’ differentiated demand for indoor thermal comfort. The regions were then classified according to the suitability of the technology for these. The results showed that the indoor heating energy consumption was high and the indoor thermal environment was not ideal, yet the solar energy resources were abundant. Indoor comfort temperature indexes that match the functional rooms and usage periods were proposed. For the buildings with the optimized combination scheme, the average indoor temperature was increased significantly and the temperature fluctuation was decreased dramatically. Most regions in Northwest China were suitable for the development of passive solar heating technology. Based on the obtained suitability of the technology for the regions of Northwest China, these were classified into most suitable, more suitable, less suitable, and unsuitable regions.

A SIMULATION BASED STUDY OF ENERGY CONSERVATION OF RESIDENCES IN LAHORE, PAKISTAN

A house in composite climate of Lahore (Pakistan) needs intensive cooling in summers; energy recovery ventilation to reduce humidity during monsoon and comfortable indoor temperature during winters. All these conditions have to be fulfilled with a reduced load on energy resources. Recent trends in construction and design of residential buildings in Pakistan symbolize uncontrolled use of energy resources. There is no data available with planning and developing authorities of housing sector that shows an account of energy loads of built houses. The potential of conservation of energy will be analyzed by actually studying the cooling and heating loads of recently constructed houses
 Key Words: Energy Conservation Potential, Module Study, Simulations

Synthesis and characterization of novel yellow-green Al-doped Y3Fe5O12 nano-pigments with high NIR reflectance

The pigments with high near-infrared (NIR) reflectance hold great promise toward both fundamental types of researches and applications for the realization of comfortable indoor-temperature by mitigating urban heat island effect. However, the facile yet simple method for the NIR reflective pigments with bright color and non-toxic feature remains a huge challenge, limiting their practical application. Herein, we proposed a mild and universal method of solution combustion for constructing the non-toxic and NIR reflective yellow-green pigments of Al-doped Y3Fe5O12. The Y3Fe4AlO12 pigment presented a high NIR reflectance of 87.66%, and an outstanding acid/alkali resistance. Moreover, the pigment had an impressive color performance (L* = 78.72, a* = − 4.05, b* = 40.04). Besides, the practical near-infrared reflection performance revealed that the transient surface temperature of the Y3Fe4AlO12 pigment was 7.6 °C lower than that of the pigment with similar color on the market. This research supplied high NIR reflecting pigments of Y3Fe5−xAlxO12 as promising coatings for roofs and exterior walls of buildings, acting as a favorable solution for urban heat island effect.

Performance of energy storage system containing cement mortar and PCM/epoxy/SiC composite fine aggregate

An enormous amount of energy is required to maintain a comfortable indoor temperature. This increases carbon dioxide emission, which is problematic. Phase-change materials have been widely used to resolve this problem and improve the energy efficiency of buildings. However, phase change materials have a fundamental drawback—leakage and low thermal conductivity. A novel thermal energy storage aggregate (TESA) was developed to solve the drawbacks of zeolites impregnated with paraffin wax and coated with epoxy resins, silicon carbide, and silica fume. A mortar which 100% replacement of TESA presented compressive strength that achieved the requirement for building material. To investigate the thermal properties, thermogravimetric analysis (thermally stable below 142 °C), differential scanning calorimetry (melting point: 36.46 °C, freezing point 46.39 °C, latent heat storage capacity: 19.76 J/g), thermal conductivity and thermal behavior of mortar measurements were conducted. Thermal shock cycling was tested to evaluate the reliability of the TESA. Finally, the thermal energy storage performance was evaluated by laboratory-sized cell tests. A laboratory-sized cell test was conducted using a self-designed room model that resemble the actual construction. The indoor temperature of the cell specimen via 100% integration of TESA, reduced the maximum temperature during the heating period by approximately 22% compared with the control cell specimen. The experimental results indicate that TESA can be applied to wall-plastering cement mortar, reducing energy consumption by decreasing the indoor temperature and reducing the temperature fluctuation.

Using Phase Change Materials (PCMs) in a Hot and Humid Climate to Reduce Heat Gain and Energy Consumption

Twenty percent of the world’s energy is consumed by the construction sector, including commercial and residential buildings, where 13% is consumed by the residential sector only. Half of the total energy consumed by buildings in Saudi Arabia is specifically attributed to the hot summer season, which, unlike in many other countries in the Middle East, continues for more than 5 months annually. The use of a phase change material (PCM), as an insulator in building materials, can be a solution to provide a comfortable indoor temperature and reduce energy consumption. This study examined two different melting ranges for PCMs RT35 and RT35HC inserted into hollow clay bricks to investigate their thermal behavior and heat storage capacity and compare them with polystyrene foam. To perform this experiment, four chambers were constructed using cement plastering. The data were collected at Jeddah, Saudi Arabia, from mid-November 2020 to the end of February 2021. When the highest temperature was reached during the experiment, PCM RT35 provided a better cooling effect by 13% compared to 24% and 28.56% for PCM RT35HC and foam, respectively, compared to hollow bricks alone. However, when the lowest temperature was reached during the experiment, PCM RT35HC performed better than the other chambers in saving energy and keeping the chamber warm, which was 9.5% for the reference chamber, 7.0% for the foam chamber, and 2.8% for PCM RT35. The maximum energy saving of PCM RT35 was around 1920 kJ, which is around 0.533 kWh, for one wall only, and for PCM RT35HC, it was 2880 kJ, or 0.8 kWh, which can reduce energy consumption of the HVAC system by 97 kWh/m2 and 146 kWh/m2 per year, respectively.