Average Indoor Temperature Research Articles

Coupled heat transfers resolution by Monte Carlo in urban geometry including direct and diffuse solar irradiations

Modelling transient combined heat transfer in complex urban geometry is a key step to predict human exposure or energy consumption and to quantify the effect of climate change mitigation and adaptation measures. A difficulty lies in the possibility for a model to scale up and integrate large and complex urban morphology. We develop a probabilistic approach to solve heat transfers with the Monte Carlo method that is insensitive to the complexity of both the urban geometry and the boundary conditions. The integral formulation that includes random walks for each heat transfer mode is presented and the computation of absorbed solar irradiations at walls with the double randomization technique is detailed. Numerical validations are given through comparisons with deterministic method results for single and two-layer slabs, but also a three-dimensional thermal bridge geometry. The developed probabilistic heat transfer model is then used in a demonstration heat wave scenario where are computed: the outdoor mean radiant temperature showing the influence of trees; and the indoor average wall temperature showing the influence of solar gains through windows.

Intelligent Green Building Design and Management Based on the Internet of Things: An Empirical Study on Low Carbon Development

This article explores the application of Internet of Things technology in intelligent green buildings through empirical research, and analyzes its practical effects in improving building energy efficiency and reducing carbon emissions. The study adopted data collection and analysis methods, and the experimental results showed that IoT technology can effectively optimize building energy management and achieve low-carbon development goals. This article designed four experiments to explore the application of Internet of Things technology in the design and management of intelligent green buildings. In the energy consumption comparison experiment, after the implementation of the Internet of Things system, power consumption decreased from 1000 kWh/day to 800 kWh/day, water usage decreased from 650 liters/day to 500 liters/day, and natural gas consumption decreased from 400 meters ³/ Days reduced to 300 meters ³/ Heaven. In the indoor environmental quality monitoring experiment, after implementing the Internet of Things system, the average indoor temperature was maintained at 22°C, humidity was 50%, and CO2 concentration was reduced to 600 ppm. In the response efficiency testing experiment of the automation control system, the average response time of the system was 2 seconds, and the response accuracy reached 90%. In the final economic benefit analysis experiment, the total savings within one year after implementing the Internet of Things system reached 12267 US dollars. From the data conclusion, it can be seen that IoT technology can not only improve the energy and environmental management efficiency of buildings, but also have significant economic benefits, providing strong support for the development of green buildings.

Radiative cooling ventilation improvement using an integrated system of windcatcher and solar chimney

The escalating crisis of non-renewable energy sources is a critical universal concern due to its adverse impact on global warming. Addressing this situation calls for strategically implementing passive cooling techniques in building design. Radiative cooling (RC), an emerging method, offers potential due to its capacity to integrate seamlessly with complementary passive strategies. This study endeavors to combine one of these ventilation techniques from ancient Persian architecture, known as the windcatcher with RC in the form of an innovative roof radiative cooling (Windcatcher-RC) with a solar chimney (SC), yielding two configurations based on the arrangement of these constituents, namely SC/Windcatcher-RC and SC + Windcatcher-RC. These designs underwent rigorous assessment within identical situations and were applied to single- and two-story buildings. This Comparative evaluation aimed not only to discern the most optimal cooling and ventilation strategy for each architectural typology but also to validate the proposed passive cooling system’s efficacy. The case studies were simulated utilizing Computational Fluid Dynamics (CFD) through the ANSYS Fluent 2021 software. The results indicate that, for single and two-story buildings, the favorable approaches are SC/Windcatcher-RC and SC + Windcatcher-RC, respectively, owing to their attainment of 8.3 and 7.8 Air Changes per Hour (ACH) in terms of ventilation, alongside their capacity to average indoor temperature reduction of approximately −3 °C during peak hours as thermal performance. This system is also able to save 60% cooling energy and 80% of the ventilation energy during peak hours in a warm and arid climate. Furthermore, the effects of a wall opening on ventilation and thermal efficiency were examined.

Application of artificial intelligence control in the control system of cooling and heating energy stations

In order to understand the application of artificial intelligence in the control system of cold and hot energy station, the author proposes a research based on artificial intelligence control in the control system of cooling and heating energy station. The author first introduces artificial intelligence technology on the basis of heating and precision heating, relies on the ?Internet plus? and IoT platform, applies indoor temperature measurement technology, intelligent control and information docking technology, and establishes a heating system based on artificial intelligence technology. This system has improved the level of enterprise management, promoted the further development of heating and intelligent energy conservation, reduced energy consumption, reduced pollution, and achieved the need for precise heating of the pipe-line network. Secondly, combined with the application case of a district, this district is selected as the application pilot to describe the role and effect of this system in the Hydronics. The experimental results indicate that the heat consumption of the residential area is 27.07 W/m2, while the heat consumption of the comparison residential area is 28 W/m2. Through indoor temperature measurement, it was found that the average indoor temperature of the comparison residential area is 22?C. Therefore, the application of artificial intelligence heating systems has improved the thermal comfort of residents, bringing users a high quality heating experience while relatively reducing energy consumption. The intelligent application of the Hydronics can more accurately grasp the heating situation, timely and efficiently adjust the heating scheme, achieve heating balance, and improve the utilization efficiency of heat sources. At the same time, it can also effectively improve the troubleshooting ability of the hydronics, prevent safety risks, improve management efficiency, and will certainly provide more powerful support for the energy-saving society and environment-friendly society.

Comparison of Heat Treatments by Floor Heating and Fan Heating for Bed Bug Control

Background: Non-chemical methods are as important as pesticides to control bed bugs. The most effective method is heat treatment. Underfloor heating is widely used in residential buildings in Korea, and the benefits of floor heating can be utilized in heat treatment for bed bug control.Methods: Simulations of indoor air flow and heat transfer were performed to compare and analyze the temperature distributions with different heating methods for bed bug control using floor heating and fan heater methods.Results: Even though the average indoor temperature of floor heating was lower, it was more uniform with floor heating than that of fan heating under the assumed conditions. Local cold spots disappeared with the floor heating method.Conclusions: It was confirmed that floor heating has advantages over fan heating to achive uniform high temperatures during heat treatment for exterminating bed bugs.

Transient thermal modelling of a Mediterranean greenhouse for sustainable agriculture: Comparison of desert and dry-summer subtropical climates

Climate change has become increasingly dominant in recent years and threatens food production and security in many areas worldwide. Due to the increase in temperature in some regions, there is a drought problem in agricultural food production, causing issues for food security. Intergovernmental Panel on Climate Change reported that climate change causes a reduction in crop quality and yield changes in farmer livelihoods. Greenhouse agriculture is a common and more protected farming management system than open-field farming. However, the influence of different climate regions on agricultural production in greenhouses should be investigated. In this study, thermal modeling of a greenhouse with and without ventilation is performed to determine the temperature and humidity variations of the greenhouse indoor air variations in selected provinces from Türkiye and Qatar to represent the effects of different climate regions. The impacts of variable climatic conditions on the greenhouse’s indoor and agricultural plants’ temperatures are investigated. Furthermore, implementing a heat pump as heating and cooling equipment in the greenhouse is studied. The yearly average vegetation and indoor temperature, respectively, are determined as 31.41 °C and 30.04 °C for Doha and 21.69 °C and 20.43 °C for Izmir. While the annual average unconditioned indoor temperature is found as 30.04 °C, the average conditioned indoor temperature is determined as 23.67 °C in Doha City. Moreover, the combined climate control mechanisms reduce the number of hours out of the optimum temperature range from 8013 to 1.4 and from 2640 to 3.1 in Doha and Izmir, respectively.

Simulation optimization and energy consumption evaluation on the wood solar drying kiln with heat storage and dehumidification system

The conventional wood drying process has high energy consumption and detrimental environmental impact. While solar energy has found widespread application in material drying, simulation software has been instrumental in optimizing drying processes and curbing energy consumption. Nevertheless, there remains a dearth of simulation and optimization studies specifically focusing on wood drying systems, particularly those incorporating phase-change heat storage devices.This study delves into the wood drying process in one year within a solar drying kiln equipped with a phase-change heat storage and dehumidification system. The investigation scrutinizes the impact of different operating parameters and heat storage devices on the temperature distribution across the entire system. Results indicate that through a new programming method, the simulation of the temperature change of the phase change thermal storage material is realized, and the visualization degree of the system is improved. The average relative error of simulated temperature and measured temperature is 2.29 %, which has a strong consistency. When dehumidifier air flow rate is 1500 m3/h, solar panel angle is 36°, the dehumidifier is turned off when the drying room temperature reaches 55 °C, and the dehumidifier is turned on when the drying room temperature drops below 55 °C, the highest energy efficiency can be achieved. Moreover, through simulation and optimization, the average indoor temperature increased by 24.05 %, and the system energy consumption reduced by about 56.23 %. This is equivalent to a reduction of 3,312.22 kg of CO2 emissions.In essence, this study provides a pathway for enterprises to realize tangible energy savings and emission reductions in the wood drying process, showcasing the potential of integrating solar energy, phase-change heat storage, and dehumidification for enhanced efficiency.

Space-Level air conditioner electricity consumption and occupant behavior analysis on a university campus

In China, despite only 2 % of the population residing on university campuses, these campuses account for 8 % of the total energy consumption. Understanding the space-level energy consumption characteristics and energy-related occupant behaviors on a university campus can help improve campus buildings' energy efficiency. This study investigates 21 office spaces on a university campus to better understand the space-level electricity consumption of air-conditioners (AC) and the occupant behaviors (OB), thermal comfort needs, and window operation. First, Internet of Things (IoT) sensors were installed in the 21 office spaces to collect the indoor temperature and humidity, the electricity consumption of the AC, and the status of doors. The data were collected for the entire cooling season. The space-level occupancy patterns were then analyzed based on the quality of the doors, including the first occupant’s arrival time and the last occupant’s departure time. Moreover, the indoor temperature, humidity, and illuminance were combined to evaluate occupants’ thermal and visual comfort need. In addition, statistical and clustering analyses were conducted on air conditioner operations' duration, frequency, and electricity consumption. The results showed that the spaces were typically occupied from 9:21 to 22:25, with 10 h and 53 min daily. The average indoor temperature was 26.1 °C, ranging from 22.1 °C (5th percentile) to 34.9 °C (95th percentile) when the room was occupied and ranging from 21.7 °C (5th percentile) to 32.5 °C (95th percentile) when the AC was on. The air conditioner's electricity consumption ranges from 11.7 to 152.2 kWh/m2 with a median of 68.9 kWh/m2 and from 46.84 to 1883.7 kWh/person with a median of 464.7 kWh/person. The different occupancy densities often lead to a significant difference in the electricity consumption of air conditioners. The findings of this study can be used to support the development of prototype energy models and occupant-centric control (OCC) models for campus office buildings.

Benefits and thermal limits of CO2-driven signaled windows opening in schools: an in-depth data-driven analysis

In the post-pandemic era, Signaled Manual Airing (SMA, i.e. windows opening driven by alarms and real-time IAQ measurements) is still expected to play a role in schools, either independently or in support of mechanical ventilation (MV) systems, as a cost-effective solution to meet more stringent regulatory requirements for indoor CO2 levels. The present study in-depth evaluates the impact of SMA on improved levels of CO2 but also its thermal downside in winter via a dedicated IoT-IAQ monitoring platform equipped with fully tuneable multi-threshold alarm schemes. An aged middle-school building, representative of a large amount of old existing school buildings in Italy (and Europe) and a Northern Italy location, were selected to investigate cold and high humidity winter conditions as the most critical for SMA. The mean indoor CO2 difference with reference classrooms without alarms ranged from 20% to an impressive nearly 70% reduction. We demonstrate a clear dependence on signalling mode and level of system usage learning. The best results were in fact attained with acoustically enhanced signalling (acu-SMA). As a downside effect, operating SMA at even moderately cold latitudes caused also thermal discomfort during the coldest days, with worsened response to the alarms. The observed mean CO2 levels maintained by classroom groups appear to be correlated with the average indoor temperature and its inverse product [CO2*Tindoor]-1 to a cumulative fatigue function with memory effect, referred as “thermal behavioural fatigue“. Bounds of generalization, further developments towards hybrid ventilation solutions and most suitable Italian regions for operating SMA in schools are finally discussed.

Employing a fan to improve the wintery heating performance of solar air collectors with phase-change material: An experimental comparison

Solar Air Collectors integrated with Phase-Change Material (SAC-PCM) were widely used for wintery heating with the superiority of overcoming the mismatch shortcoming between supply and demand time from solar heating. However, the traditional SAC-PCM had the low-efficiency heat output due to the low air flow of natural convection. Based on this, a fan was proposed to enhance air flow and thereby, increase the heat output from SAC, so an experiment was built to compare the thermal performance between SAC-PCM and SAC-PCM with a fan (SAC-PCM-F). The experimental result showed that the fan enhanced the outlet wind speed from 0.8 m/s-1.55 m/s to 2.15 m/s-2.3 m/s and by employing the fan, the heat output was easier from SAC-PCM and the average temperatures of outlet air were increased 4.18 °C in all day with the average temperature difference of outlet and inlet air increased by 1.17 °C. Employing the fan could improve indoor average temperature by 1.17 °C, while the daily heat output was increased by 146.02% by employing the fan and the heat collecting efficiency was increased from 24.92% to 61.32%

Indoor temperature prediction with context-aware models in residential buildings

This paper presents a novel approach for predicting average indoor temperature in residential buildings, utilizing contextual factors of the rise of the building and geographical location. The proposed approach employs advanced deep learning architectures, such as Long Short-Term Memory (LSTM) and Transformers, to create generalized predictive models applicable to a range of residential buildings. The models are trained using historical data from 18 residential buildings over a period of 6 to 10 years, where the buildings are located in different climate zones. Testing is done on nine different data sets representing three different locations and three different types of buildings. The study demonstrates that incorporating the context of building rise significantly improves the models’ predictive performance. Specifically, the transformer-based models show improvements in R2 of 4%–27% in a 6 h prediction horizon. The proposed approach explicitly using context information significantly improves the accuracy of predicting, making learnt models a good starting point for optimizing district heating distribution.

Experimental investigation on cooling surface heat transfer behavior of a thermally activated building system in warm and humid zones

Thermally Activated Building System (TABS), is one of the alternative cooling methodology, due to the numerous advantages it provides the building industry. This system consists of encapsulated pipes within the building structure to control the surface temperature, which helps to remove the sensible heat from the indoor. The objective of this investigation is to experimentally evaluate the influence of cooling surface area and the effect of cooling water inlet flow velocities on the TABS performance in the warm and humid zone under natural ventilation, and the experimental results were compared with the conventional building (CB), which does not have any cooling arrangements. An increase in water inlet velocity from 0.35 to 1.5 m/s substantially removes the thermal energy stored in the TABS, and reduces the average indoor temperature by 3 °C. In a CB, the average heat gain of all surfaces varies from −3 W/m2 to 13 W/m2. Moreover, in all surface cooling (ASC), it varied from −2 W/m2 to 24 W/m2. This resulted in increased surface cooling, which increased the surface heat gain and indoor cooling capacity. There are no significant thermal behaviour and heat transfer variations at 1 m/s and 1.5 m/s of inlet water flow velocities.

Assessment of natural ventilation strategy to decrease the risk of COVID 19 infection at a rural elementary school

Natural ventilation in low-budget elementary schools is the main focus to ensure the health and comfort of its occupants, specifically when looking at the global pandemic related to SARS-COV-2. This paper presents an experimental and novel study of natural ventilation in a public elementary school (Los Zumacales), with a particularly low economic budget. The study was carried out during the winter months of the Covid 19 pandemic. The school is located in the rural area of Castilla y León (North-Western Spain) far from high traffic roads. In this study, a methodology of measuring CO2 concentration was applied in nine classrooms in a school. The experimental study shows the level of natural ventilation in each classroom, expressed in Air Changes per Hour (ACH), using the Decay CO2 concentration method. The method is proven by comparing the experimental values of the obtained ACH with those determined by the most powerful methods to achieve appropriate ventilation levels. Thus, ensuring health protection protocol in rural schools, against the COVID 19 pandemic. Harvard guide and Spanish regulations (RITE), two widely recognized methods have been used together with the experimentally obtained standard by Rey et al. Only one classroom showed a value lower than 3 indicating poor ventilation. In this study, the degree of thermal comfort in the nine classrooms were also analyzed according to the EN15251 standard. An average indoor temperature of approximately 19 °C was obtained, and the relative humidity was stable and correct according to Spanish regulations. In addition, the risk of infection in each classroom was estimated following the international method recommended by the federation of European Heating, Ventilation, and Air Conditioning Associations (REHVA). The probability of infection in all the cases studied was less than 14%. Therefore, this study provides a strong response against infections illnesses, such as Covid 19, in educational buildings where economic budgets of their facilities are low in both, maintenance and investment.

The Numerical Study on Indoor Heat and Moisture Transfer Characteristics of an Ancient Palace Building in Beijing

The heritage of ancient buildings is an important part of the world’s history and culture, which has extremely rich historical–cultural value and artistic research value. Beijing has a large number of ancient palace buildings, and because of the age of their construction, many of them have problems with varying degrees of peeling and molding on the inner surfaces of the envelope. To solve the problems of damp interiors of palace buildings, a mathematical model of indoor heat and moisture transfer was established based on an ancient wooden palace building in Beijing. The model was validated by fitting the measured and simulated data. And the effects of outdoor relative humidity, soil moisture, wall moisture, and other factors on indoor heat and moisture transfer of ancient buildings were simulated and analyzed via the control variables method. The results showed that the measured and simulated data are within the error range, which verifies the accuracy of the model. And the simulation of indoor humidity matched the measured humidity. Thus, the simulation results were consistent with the actual situation. The variable trend of the relative humidity of the indoor environment with the outdoor humidity is inconsistent from plane to plane, i.e., it increases or remains constant with the increase in the outdoor humidity. Indoor ambient relative humidity increased with increasing wall moisture. And the indoor average temperature is 24.5 °C, and indoor relative humidity ranged between 87.4% and 92.4%. Soil moisture and wall moisture were the main factors affecting indoor relative humidity.

Indoor thermal comfort analysis of TABS with untreated natural ventilation in a warm and humid climate – An experimental study

BackgroundThermally activated building systems (TABS) are the most environment-friendly and energy-efficient cooling technology. These cooling methods, which use pipe-encapsulated building surfaces to minimize the indoor cooling load, have been used in this work. The primary objective of the research is to measure the energy use, thermal comfort and the impact of cooling surface area and water inlet flow velocities on the performance of TABS with natural ventilation assistance in a warm and humid environment. MethodsExperimental studies were conducted to investigate the impact of cooling surface area and water inlet flow velocities on the performance of thermally active buildings with natural ventilation assistance. Significant findingsNatural ventilation had a significant impact on advancing and increasing the average indoor air temperature by 1.5 °C when compared to the neutral adaptive comfort band. The increase in the water inlet velocity from 0.35 to 1.5 m/s substantially removes the thermal energy stored in the TABS system by reducing the average indoor temperature by 2 °C. The predicted percentage dissatisfied (PPD) was approximately 40% of all cooled surfaces. The energy consumption for 1 m/s water inlet velocity, which provides similar thermal comfort for higher flow rates, is 1.3 kWh. Therefore, from the study, 1 m/s water inlet velocity is found to be the optimal value, where comfort and energy consumption are within an acceptable range. Hence, the operating parameters under which the building envelope is cooled would significantly impact the performance of the thermally activated building system.

Research on the indoor temperature regulation characteristics of a nearly zero energy building with the nonlinear heat capacity building components: A simple model

With establishment of global carbon reduction targets, energy conservation and emission reduction of building is imperative. By passive building design method, nearly zero energy buildings (nZEB) can decrease building energy consumption requirements. To reduce indoor temperature fluctuation of the nZEB in heating season, the conventional energy storage materials (CESM) or phase change materials (PCM) are utilized in the building components for thermal storage. The heat capacity of the PCM was simplified as ideal nonlinear heat capacity. To reveal the indoor temperature distribution characteristic in the nZEB affected by the building components with or without the nonlinear heat capacity, a simplified mathematical model was established. Several evaluation indicators were put forward to describe indoor temperature regulation difference between the CESM and the PCM. The results show that indoor temperature distribution characteristics of the nZEB with PCM was significantly different with that of the CESM building. The maximum indoor temperature distribution frequency of the PCM building is much larger than that of the CESM building. The maximum indoor temperature distribution frequency of PCM building was more concentrated and occurred close to the phase transition temperature. The maximum indoor temperature distribution frequency of the CESM is not exceed 10%, however, that of the PCM building can reach 42% in the same work condition. The maximum indoor temperature distribution frequency, the indoor comfort guarantee ratio and the latent heat utilization time ratio of the PCM building can be obviously increased by selecting the phase transition temperature close to the average indoor temperature in the heating season. The study work represent that the PCM building components with the nonlinear heat capacity can regulate the indoor temperature distribution frequency by change phase transition temperature.

Simulation Analysis of High Radiant Heat Plant Cooling and Endothermic Screen Waste Heat Recovery Performance Based on FLUENT

In this article, we propose the endothermic screen model. The aim is to reduce the problems of the high temperature and low utilization of waste heat in industrial plants with high radiant heat. In this paper, the Rhino software is used to establish the model and import it into the FLUENT software, divide the mesh, set the boundary conditions and analyze the transient temperature field. Finally, the temperature change law in the plant and the waste heat recovery efficiency of the endothermic screen are obtained. The flow of cooling water in the endothermic screen is used to transform and transfer the high-radiation heat inside the plant to the outside. The simulation results show that after adding the endothermic screen, the average indoor temperature drops from 313.33 K to 305.66 K, which has a cooling effect. The waste heat recovery efficiency reaches up to 56%, and the waste heat recovery effect is obvious. The research results can provide a reference for the application of an endothermic screen in actual high radiant heat plants and provide a more comfortable working environment for the plant workers.

Cold homes in Australia: Questioning our assumptions about prevalence

Australia is considered by many to be a warm climate country and hence winter cold and its health effects are often overlooked. The majority of the Australian population live in temperate climate regions, which are heating-dominated and experience cold wintertime conditions. The prevalence of cold in Australian homes has to date been rarely measured or estimated, and the few studies that do are based on proxy data that estimate a low prevalence (around 5 %). This paper tests these proxy measures, using high resolution temperature data on indoor temperature from 100 homes across temperate Australia. The data were assessed using the World Health Organization's Housing and Health guideline for minimum indoor temperature (18 °C), which provides an internationally recognised benchmark for defining cold in homes. Across the sampled homes, 81 % were below 18 °C on average across the whole of winter (June–August 2022). Average winter indoor temperatures were 16.5 ± 2.7 °C across all homes, with no significant difference between locations. These early findings suggest that the problem of unhealthily cold homes in Australia is likely to be significantly more prevalent than previously estimated. Far from affecting 5 % of Australian households, the affected population may be 10 times this value. These initial findings have important implications for how we model health impacts and develop policy. This early release data from a recently commenced large environmental monitoring project is of timely importance. It challenges our understanding of the prevalence of cold housing in Australia context, flagging the pressing need to increase policy attention in advance of winter.

Performance of a novel internal insulation in Chinese solar greenhouse for the cleaner and energy-saving production in high latitudes and cold regions

Chinese solar greenhouse (CSG), which facilitates year-round vegetable cultivation without energy consumptions or carbon emissions, is significant for sustainable agriculture. However, the overwintering production is often damaged by frost in high latitudes and cold regions. Since as much as 60% of the heat is lost from the front roof, a novel internal insulation was proposed to improve the thermal insulation capacity of the unheated CSG. The traditional single-layer front roof was transformed into comprehensive external and internal thermal insulation to reduce nighttime heat dissipation. The mathematical model and the energy balancing equations were established to clarify the theoretical basis and evaluated the effectiveness of the proposed method through experiments. The results indicate that the internal insulation helped reduce the heat loss of the front roof by 13.67% and the total heat saving in CSG was 8.75%. The average indoor temperature was improved by 2.01 K, and the difference with outdoor temperature could reach 36.26 K. The economic benefit 36.93 USD per day for winter production. The results can provide scientific evidence for the system design of internal insulation in solar greenhouses or other agricultural settings, in order to guarantee the cleaner and energy-saving production of annual vegetable supply in high latitudes and cold regions.

Indoor thermal comfort evaluation of traditional dwellings in cold region of China: A case study in Guangfu Ancient City

Global climate change has led to increased differences in the indoor thermal environment of traditional dwellings and residents' thermal adaptability, but quantitative research in this area needs to be updated and improved. In this paper, taking the old and new types of traditional dwellings of Guangfu Ancient City in Hebei province, China as the example, we first investigated the current situation of indoor thermal environment and thermal comfort characteristics of residents by means of subjective questionnaire survey and objective data measurement. The measured data showed that the average indoor temperature of old-type traditional dwellings in winter was far lower than the thermal comfort range of human body, and it was also higher than the relevant standard in summer. Secondly, we established a new thermal comfort evaluation model of traditional dwellings and proposed a new thermal neutral temperature of residents: old-type traditional dwellings (18.1 °C in winter and 27.1 °C in summer), new-type traditional dwellings (19.8 °C in winter and 25.7 °C in summer). Although the measured data showed that the thermal environment quality of the old-type traditional dwellings was poor, the residents had strong thermal adaptability. Finally, we put forward the different living performance improvement strategies of old and new types of traditional dwellings: The old-type traditional dwellings should focus on strengthening the thermal performance of the envelope structure, while the new-type traditional dwellings should solve the problem of low indoor humidity in winter. This research improves the evaluation system of human thermal comfort of dwellings in cold region of China, and provides a good case reference.