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.
Humans spend approximately 70–90% of their lifetime indoors, particularly the sick, weak, disabled, and elderly [
Indoor temperature plays a vital role in the achievement of a comfortable indoor thermal environment. Additionally, building standards [
The indoor temperature directly affects indoor thermal comfort and building energy consumption [
As is widely known, the application of passive solar heating technology can enable buildings to achieve certain heating functions without the aid of mechanical power. Given this, many scholars have conducted studies on passive technologies. It has been demonstrated that the application of passive solar heating technology can significantly improve the indoor environment and reduce building energy consumption [
As a rapidly-developing country, China’s construction industry is undergoing rapid development and innovation. Nevertheless, the existing schemes for improving the thermal environment of rural dwellings are imperfect. The problems of low indoor thermal comfort and high heating energy consumption continue to be prominent [
The investigation of the suitability of passive solar heating technology involves an analysis of the building thermal process under geographical zoning. An issue that needs to be focused upon while discussing building thermal processes is the heat transfer in the building envelope. To clarify the heat transfer condition of the envelope, it is necessary to solve the differential equation of heat conduction. The solving of the equation involves its discretization. At present, the commonly used discretization methods include the finite-volume method (FVM), finite-element method (FEM), and finite-difference method (FDM). However, a comprehensive comparison revealed that the FVM has a low computational accuracy [
In addition, the two main specialized computer-aided engineering software programs for building thermal simulation are EnergyPlus and DesignBuilder (DB). EnergyPlus is a building energy simulation engine developed by the U.S. Department of Energy and Lawrence Berkeley National Laboratory. It is based on the building heat balance equation and the FDM to analyze building thermal performance, solar energy utilization scheme, and indoor temperature fields under unsteady heat transfer [
To develop a comfortable and energy-efficient indoor thermal environment, this study undertook the following tasks with the rural dwellings in Northwest China as the research object:
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. The indoor comfort temperature indexes that match the functional rooms and usage periods were explored. A comprehensive passive optimized design of existing buildings is conducted, and the validity of the optimized combination scheme was explored using DB. The suitability of passive solar heating technology for each region in Northwest China was analyzed using the obtained differentiated comfort temperature indexes. Furthermore, the regions were classified according to the suitability of the technology.
Ningxia is located in inland Northwest China (
The field survey revealed two types of local rural dwellings: earth buildings (7%) and brick-concrete buildings (93%). A majority of the local dwellings were approximately square. The internal and external walls were made of solid clay bricks. The thicknesses of the internal and external walls were 370 mm and 240 mm, respectively. The external walls were decorated with 10 mm-thick white tiles or fair-faced concrete. The internal walls were painted with lime mortar. The roof was generally single sloped or double sloped. Only the bedroom had a suspended ceiling (gypsum board). The windows were generally made of single-glass aluminum alloy. The door and indoor door were made of aluminum alloy and wood, respectively. A representative brick-concrete dwelling (
The test site was located in Heilin Village, Ningxia, Northwest China. The data were collected from January 16 to 20, 2015. The solar radiation intensity, relative humidity and temperature of air, air velocity, and black-globe temperature were measured. Considering the complexity involved in the measurement, the mean radiation temperature was assumed to be approximately equal to the black-globe temperature [
Instrument | Type | Test parameters | Range | Accuracy | Symbol |
---|---|---|---|---|---|
Temperature and humidity recorder | TESTO175-H | Temperature | −20°C∼55°C | ±0.4°C | ▴ |
Relative humidity | 0%∼100% | ±2% | |||
Black-globe thermometer | HQZY-1 | Black-globe temperature | −20%∼80°C | ±0.3°C | ● |
Hot-bulb anemometer | ZRQF-F30 | Air velocity | 0.05∼30 m/s | ±(4%U ± 0.05) m/s | ♦ |
Solar radiometer | JTDL-4 | Solar radiation intensity | 0∼2000 W/m2 | 0.1 W/m2 | ▪ |
The measurement duration of solar radiation intensity was 10 h, and the acquisition time interval was 1 h. The measuring point was located outdoors without shelter. The monitoring period for the relative humidity and temperature of the air was 24 h, and the acquisition time interval was 10 min. The measuring points are approximately 1.1 m above the ground.
The mean radiant temperature and air velocity were not recorded continuously owing to the inconvenience of placing the black-globe thermometer and hot-bulb anemometer in the respondent’s home for a long time. The mean radiation temperature and air velocity were measured every 2 h. The globe thermometer and hot-bulb anemometer were placed approximately 1.1 m above the ground.
Verbal and written informed consent was obtained from the participants prior to the questionnaire survey. The participants were villagers who had lived in the region for a long time. To ensure that the participants completed the written questionnaire conveniently and effectively, each question in it was explained before they executed it. In the experiment, the participants were asked to maintain daily habits and emotional stability. They were paid after they had participated in the entire experiment. In addition, to induce the participants to support this experiment, we assured them that positive performers would be provided additional rewards.
The data were collected during January 16–20, 2015 and January 15–17, 2017. A total of 610 participants were received face-to-face questionnaires. Finally, 583 valid questionnaires were recovered, which corresponded to an effective recovery rate of 95.6%. The questionnaires included basic life information and subjective perceptions of the participants. The thermal sensation votes (TSVs) were determined using the ASHRAE 7-point scale [
The thermal parameters and construction methods of the existing rural houses in Ningxia were optimized by combining the building standards [
Component | Design parameters and construction methods |
---|---|
Type of building | Single story, rural dwelling |
Total height | 3.5 m |
Construction area | 15.02 m × 8.54 m, 15.02 m × 8.90 m, 15.02 m × 9.82 m |
{{External wall}} | Cement/plaster/mortar 10 mm, lime |
Internal wall | Gypsum plastering 10 mm, cement/plaster/mortar 10 mm, lime-sand brick 240 mm, cement/plaster/mortar 10 mm, gypsum plastering 10 mm, U = 0.45 W/m2⋅K |
Gypsum plastering 10 mm, cement/plaster/mortar 10 mm, lime-sand brick 240 mm, cement/plaster/mortar 10 mm, asphalt-reflective coat 3 mm, U = 0.42 W/m2⋅K | |
{{Roof}} | Gypsum plastering 10 mm, cement/plaster/mortar 10 mm, reinforced concrete 100 mm, EPS (Expanded polystyrene) 90 mm, cement/plaster/mortar 10 mm; asphalt mastic roofing 3 mm, roof tile 25 mm, U = 2.76 W/m2⋅K |
{{Ground}} | Cement plaster, sand aggregate 15 mm, EPS (Expanded polystyrene) 30 mm, cast concrete 100 mm, floor screed 7 mm, timber flooring 3 mm, U = 1.12 W/m2⋅K |
{{Glazing}} | Double clear 6 mm/12 air/6 mm, e = 0.1, U = 1.77 W/m2⋅K, direct solar transmittance = 0.474, solar heat gain coefficient = 0.563, light transmission = 0.745 |
Note: According to reference [
To investigate the impact of different types of passive solar houses on the indoor thermal environment, three types of passive solar houses were introduced in the design. The optimized floor plans of these three types of houses are shown in
Passive solar house style | Component | Size/m |
---|---|---|
Direct-gain window | The south window | 3.6 × 2.5 |
passive solar house | 3.8 × 2.5 | |
Trombe wall + direct-gain window passive solar house | Glass curtain wall | 4.0 × 3.0 |
4.3 × 3.0 | ||
Air layer | 0.08 | |
The top vent | 0.5 × 0.4 × 2 | |
0.5 × 0.5 × 2 | ||
The bottom vent | 1.0 × 0.4 | |
1.2 × 0.4 | ||
The south window | 1.5 × 2.2 | |
1.8 × 2.2 | ||
Attached sunspace passive solar house | Sunspace | 4.5 × 1.5 × 3.5 |
4.8 × 1.5 × 3.5 | ||
The south window | 4.0 × 2.8 | |
4.3 × 2.8 |
Northwest China includes the three provinces Shaanxi, Gansu and Qinghai and the two autonomous regions of Ningxia and Xinjiang (
No. | Region | Latitude | Zone | Class | No. | Region | Latitude | Zone | Class |
---|---|---|---|---|---|---|---|---|---|
1 | Dunhuang | 40°15′ | C | I | 15 | Tongde | 35°27′ | SC | II |
2 | Jiuquan | 39°77′ | SC | I | 16 | Madoi | 34°92′ | SC | II |
3 | Minqin | 38°63′ | C | II | 17 | Yushu | 33°02′ | SC | II |
4 | Lanzhou | 36°05′ | C | II | 18 | Yinchuan | 38°47′ | C | II |
5 | Hezuo | 35°00′ | SC | II | 19 | Altay | 47°73′ | SC | II |
6 | Tianshui | 34°58′ | C | II | 20 | Karamay | 45°50′ | SC | III |
7 | Longnan | 33°33′ | HSCW | II | 21 | wulumuqi | 43°80′ | SC | II |
8 | Yulin | 38°23′ | C | II | 22 | Hami | 42°82′ | C | II |
9 | Xi’an | 34°18′ | C | III | 23 | Turpan | 42°93′ | C | II |
10 | Hanzhong | 33°70′ | HSCW | III | 24 | Yining | 43°95′ | C | II |
11 | Delingha | 37°37′ | SC | I | 25 | Korla | 41°75′ | C | II |
12 | Gangca | 37°33′ | SC | I | 26 | Kashi | 39°47′ | C | II |
13 | Golmud | 36°42′ | SC | I | 27 | Ruoqiang | 39°03′ | C | II |
14 | Xining | 36°62′ | SC | II | 28 | Hotan | 37°13′ | C | II |
Note: Zone: thermal zone, Class: solar energy class, C: cold, SC: severe cold, HSCW: hot summer and cold winter.
Type | Typical region | Annual radiation/MJ·m–2 | The average outdoor temperature in the winter solstice day/°C |
---|---|---|---|
I-SC | Jiuquan | 6307.0 | –5.1 |
II-SC | Xining | 5603.2 | –6.9 |
III-SC | Karamay | 5153.4 | –12.1 |
I-C | Dunhuang | 6567.8 | –4.9 |
II-C | Yinchuan | 5785.1 | –4.0 |
III |
Xi’an | 4238.8 | 1.6 |
II-HSCW | Longnan | 5080.3 | 6.4 |
III-HSCW | Hanzhong | 4000.3 | 5.3 |
The residents’ demand for indoor thermal comfort was classified based on the responses to the questionnaire (see
Note | Period |
---|---|
Main functional rooms | 6:00 am to 10:00 pm (the activity period) |
10:00 pm to 6:00 am the next day (the sleep period) | |
Secondary functional rooms | 6:00 am to 10:00 pm (the activity period) |
Under natural operation, the indoor thermal environment of a building is determined by the building thermal process. This process involves a series of heat balance equations and thermal transfer equations. The heat balance equations include those of the internal (external) surface of the non-transparent envelope, internal (external) surface of the transparent envelope, and indoor air.
The heat balance equation of the external surface of the non-transparent envelope is expressed as [
where
The heat balance equation for the internal surface of the non-transparent envelope is expressed as [
where
The heat balance equation of the internal and external surfaces of the transparent envelope can be expressed as (for double-glazed windows as an example) [
where
The heat balance equation of indoor air is [
where
An issue that should be focused upon in the solution of the heat balance equation is the heat transfer by the envelope.
The indoor temperature varies continuously owing to the variation in outdoor weather conditions with time. Therefore, the heat transfer phenomenon of the envelope structure is considered to be an unsteady heat transfer process. The differential equation of unsteady heat conduction in the three-dimensional (3D) Cartesian coordinate system is expressed as [
where
However, considering that the height (length) and width of the external envelope are 8–10 times the thickness, the unsteady heat transfer of the external envelope is considered as a one-dimensional unsteady heat transfer process. The one-dimensional differential equation of unsteady heat conduction is expressed as [
where
Engineering calculation problems can be solved effectively and rapidly using the FDM. Using this method, the temperature gradient from the center of the k – 1-th (k-th) floor to the center of the k-th (k + 1-th) floor at time m is expressed as
where
Based on
where
where
Because the envelope is a homogeneous material layer,
where
To determine the specific heat transfer conditions, the initial and boundary conditions need to be specified in addition to the heat conduction equation.
The boundary condition is [
where
The initial condition is [
The finite difference equation system (matrix expression form) of one-dimensional unsteady thermal conductivity is obtained according to
Further, the sequential Gaussian elimination method was used to solve the equation system to obtain the temperature of the surface of the envelope at each moment.
The process of the simulation using DB is as follows: (1) establishment of 3D model, (2) meshing, (3) setting of parameters, (4) setting of boundary conditions, and (5) verification of the model. It was worth noting that the meshing was done automatically by the DB in the running background. Therefore, this step was not shown during the simulation.
(1) 3D models
The 3D models for the simulation were established according to
(2) Setting of parameters
The construction parameters of the building are shown in
Note | Parameter | |
---|---|---|
Number of occupants | Main functional rooms | 4 (average) |
Secondary functional rooms | 2 (average) | |
Equipment load | Main functional rooms | 8 W/m2 |
Secondary functional rooms | 6 W/m2 | |
Lighting load | Main functional rooms | 6 W/m2 |
Secondary functional rooms | 5 W/m2 | |
Air changes per hour | 0.5 times/h |
Note: (1) The rooms were classified into main functional rooms (
(3) Setting of boundary conditions
China is located in the northern hemisphere of the earth. The day with the shortest sunshine time and the lowest solar altitude angle is the winter solstice. From the perspective of passive heat collection, the solar radiation conditions on this day are the worst for the year. Therefore, the winter solstice day was considered as the simulated weather date to explore the suitability of passive solar heating technology for each region in Northwest China.
(4) Validation of the model
The correctness of the model was verified to compare the tested data with the simulated data. The tested data were the indoor temperature of the tested dwelling on January 19, 2016. The comparison results between the simulated data and the tested data are presented in
As shown in
During the test, only the bedroom had a simple heating device (coal stove). It was operated from 6:00 am to 10:00 pm. The meteorological data of a sunny day (January 19, 2015) during the test period were selected for analysis in this study.
The variations in indoor and outdoor meteorological parameters during the test are shown in
As shown in
In addition, the intermittent test results demonstrated that there was a marginal difference between the indoor mean radiation temperature and indoor air temperature (±0.5°C). The indoor airflow was significantly weak (within 0.1 m/s, which is lower than the human body’s air-flow-perception threshold of 0.2 m/s [
During the data measurement, we also surveyed the indoor heating in winter. The survey showed that most families heated only the bedrooms. Each dwelling consumed approximately 3t of coal through the coal stove during the heating period. When all the rooms were heated, the heating energy consumption would be 2–3 times the present energy consumption.
To sum up, the outdoor temperature was low, and the temperature difference in winter in this area was large. Notwithstanding the high energy consumption for heating, the indoor thermal environment was still not ideal. However, the area was rich in solar energy resources. Given this, passive solar buildings can be developed according to local conditions.
The determination of indoor comfort temperature index was influenced by the regional climate, residents’ behavior habits, psychological activities, etc. [
Using a research method that differentiates functional rooms and usage periods, a detailed investigation was carried out on the clothing conditions of rural residents in Northwest China in winter. Further, the thermal resistance of residents’ clothing during the activity period was obtained according to the ASHRAE Standard 55-2013. The results are presented in
In addition, the survey found that during the nighttime sleep period, the local rural residents were used to wearing pajamas and covering thick quilts. The thermal resistance of pajamas and thick quilts were 0.38 clo and 2.86 clo, respectively [
In summary, the thermal resistance of winter clothing of rural residents in Northwest China was large. Besides, the thermal resistance of residents’ clothing varies significantly across functional rooms. The residents’ demand for thermal resistance varies substantially across usage periods.
The activity rate of residents in a room is defined as the number of residents in the room as a percentage of the total number of individuals in all the rooms. The activity rate of residents in different functional rooms was investigated at intervals of 1 h. The activity rate of residents in different functional rooms during the activity period is presented in
Moreover, the survey found that during the sleep period (from 10:00 pm to 6:00 am the next day), only the main functional rooms constituted the activity space of the local rural residents. Accordingly, the residents’ demands for indoor thermal comfort of secondary functional rooms at night are not discussed in the subsequent analysis. Referring to the ASHRAE Standard 55-2013, the metabolic rate of residents during sleep at night was 45 W/m2. The survey also found that the local rural residents were in the period of agricultural leisure during winter. During the activity period, the activities of the residents in the main functional rooms were watching TV, chatting, and sleeping for brief periods, whereas those of the residents in the secondary activity rooms were cooking, sewing, knitting, and maintenance. The metabolic rate of residents in main and secondary functional rooms was 85 W/m2 and 95 W/m2, respectively, according to the ASHRAE Standard 55-2013.
To summarize, the activity rate of the same functional room varied across usage periods. Furthermore, the activity rates of different functional rooms varied across the same usage periods.
The temperature was grouped with 0.5°C as the group distance. For each temperature group, the thermal acceptance rate (the ratio of the number of residents with voting values of –1 to +1 as a percentage of the total number of voters) was calculated. Finally, a polynomial fit was performed on the thermal acceptance rate and indoor air temperature. The fitting results are shown in
The acceptance rate of 80% of residents is regarded as the acceptable range of thermal environment [
First, the temperature was grouped within 0.5°C as the group difference. Second, the percentage of people who expect the environment to be hotter or colder than the current environment was counted, and linear regression was performed with the air temperature, respectively. The results are shown in
The thermal comfort demands of the local rural residents varied across functional rooms during the same period. Besides, the thermal comfort demands of the same functional room varied across usage periods. Thus, the indoor thermal comfort evaluation indexes based on residents' differentiated thermal demand should be explored.
The widely used indoor thermal comfort evaluation indexes are Operative Temperature (Top), Standard Effective Temperature (SET*), Predicted Mean Vote (PMV), and Subjective Temperature (Tsub). Top was proposed as an indoor thermal comfort evaluation index based on the apparent heat transfer between the surrounding environment and human body by convection and radiation [
Based on the above analysis, it is considered that Tsub was effective and feasible as an indoor thermal environment evaluation index. It can be calculated using
where
The Tsub under different conditions was obtained based on
Note | Clothing thermal resistance/clo | Metabolic rate/W·m–2 | Subjective temperature/°C | |
---|---|---|---|---|
{{Main functional rooms}} | 6:00 am to 10:00 pm |
1.60 | 85 | 15.1 |
10:00 pm to 6:00 am the next day |
3.24 | 45 | 12.9 | |
Secondary functional |
6:00 am to 10:00 pm |
1.80 | 95 | 12.0 |
Meanwhile, the comfort temperature was estimated using Griffiths’ method, as shown in
where
Note | Comfort temperature/°C | ||
---|---|---|---|
Mean | S.D. | ||
{{Main functional rooms}} | 6:00 am to 10:00 pm |
15.5 | 1.3 |
10:00 pm to 6:00 am the next day |
12.9 | 1.2 | |
{{Secondary functional rooms}} | 6:00 am to 10:00 pm |
11.6 | 1.3 |
A comparison of
This study aims to develop a comfortable and energy-efficient indoor thermal environment. Given this, this study proposes that during the activity period (from 6:00 am to 10:00 pm), the average indoor temperature of the main and secondary functional rooms should be at least 15°C and 12°C, respectively. During the sleep period (from 10:00 pm to 6:00 am the next day), the average indoor temperature of the main functional rooms should be at least 13°C.
A comparison of the thermal comfort temperature indexes proposed in this study with the results of previous studies in Northwest China, it is found that the temperature range of the thermal comfort indexes is basically consistent [
There was no heating source in the room during the numerical simulation. Comparison of indoor temperature before and after optimization. The results are presented in
Type | Room | Maximum temperature/°C | Minimum temperature/°C | Average temperature/°C | |
---|---|---|---|---|---|
Measurement | Master bedroom | 15.0 | 6.4 | 9.6 | |
Storage room | 9.1 | 3.5 | 5.5 | ||
Simulation | Mode1 | Room1 | 16.8 | 11.0 | 13.2 |
Room2 | 10.3 | 8.9 | 9.5 | ||
Simulation | Mode2 | Room1 | 17.8 | 14.1 | 15.5 |
Room2 | 10.3 | 9.3 | 9.9 | ||
Simulation | Mode3 | Room1 | 16.1 | 15.2 | 15.6 |
Room2 | 13.0 | 12.1 | 12.3 |
For brevity, the simulation results of 8 typical regions are expounded. The simulation results of the other 20 representative regions are listed in
Region | Note | Mode1 | Mode2 | Mode3 | |||||
---|---|---|---|---|---|---|---|---|---|
Avg./°C | Fluct./°C | Avg./°C | Fluct./°C | Avg./°C | Fluct./°C | ||||
Most suitable | Room1 | AP | 14.7 | 11.5~19.7 | 15.3 | 13.8~17.4 | 16.2 | 15.8~16.7 | |
PA | 12.9 | 12.2~13.3 | 14.6 | 14.0~15.0 | 16.1 | 16.0~16.2 | |||
Room2 | AP | 11.8 | 11.2~12.6 | 12.4 | 12.1~13.4 | 12.6 | 12.3~13.3 | ||
Delingha | Room1 | AP | 16.1 | 12.1~21.1 | 16.4 | 14.2~19.1 | 16.6 | 16.1~17.1 | |
PA | 13.3 | 12.7~14.0 | 15.2 | 14.8~15.8 | 16.5 | 16.4~16.6 | |||
Room2 | AP | 12.1 | 11.7~13.0 | 12.5 | 12.2~13.3 | 13.1 | 12.9~13.9 | ||
Room1 | AP | 15.4 | 12.5~19.4 | 16.2 | 14.7~17.3 | 16.5 | 16.2~16.9 | ||
PA | 13.5 | 13.1~14.2 | 15.7 | 15.4~16.1 | 16.4 | 16.3~16.5 | |||
Room2 | AP | 12.2 | 11.8~13.2 | 13.0 | 12.4~13.6 | 13.5 | 13.2~14.2 | ||
Room1 | AP | 15.3 | 12.8~18.7 | 16.2 | 14.7~18.2 | 16.4 | 16.0~16.8 | ||
PA | 13.5 | 13.0~14.2 | 15.4 | 15.1~15.9 | 16.3 | 16.2~16.4 | |||
Room2 | AP | 12.0 | 11.7~13.1 | 12.7 | 12.2~13.5 | 13.3 | 12.9~13.9 | ||
More suitable | Minqin | Room1 | AP | 13.4 | 11.4~17.0 | 14.5 | 13.4~15.6 | 14.9 | 14.6~15.4 |
PA | 12.1 | 11.6~12.6 | 13.9 | 13.4~14.7 | 14.7 | 14.5~14.9 | |||
Room2 | AP | 10.8 | 10.3~11.6 | 11.6 | 11.4~12.3 | 11.9 | 11.7~12.5 | ||
Lanzhou | Room1 | AP | 12.9 | 11.9~16.7 | 14.3 | 13.3~15.8 | 14.8 | 14.3~15.1 | |
PA | 11.6 | 11.0~12.1 | 13.2 | 12.8~14.3 | 14.6 | 14.4~14.9 | |||
Room2 | AP | 10.5 | 10.1~11.5 | 11.2 | 10.8~11.7 | 11.7 | 11.5 - 12.3 | ||
Room1 | AP | 12.7 | 10.8~15.8 | 14.0 | 13.1~15.5 | 14.7 | 14.4~15.1 | ||
PA | 11.5 | 10.9~11.9 | 13.1 | 12.8~13.4 | 14.5 | 14.2~14.8 | |||
Room2 | AP | 10.4 | 9.9~11.3 | 11.1 | 10.6~11.6 | 11.6 | 11.3~12.1 | ||
Tianshui | Room1 | AP | 13.4 | 11.9~17.5 | 14.7 | 13.5~15.8 | 15.0 | 14.7~15.2 | |
PA | 11.9 | 11.4~12.5 | 14.0 | 13.5~14.3 | 14.9 | 14.8~15.0 | |||
Room2 | AP | 10.6 | 10.2~11.5 | 11.3 | 10.8~11.9 | 11.9 | 11.5~12.4 | ||
Yulin | Room1 | AP | 12.7 | 10.0~16.1 | 14.4 | 12.8~15.8 | 14.8 | 14.4~15.1 | |
PA | 11.6 | 11.1~12.0 | 13.3 | 12.9~13.6 | 14.7 | 14.6~14.8 | |||
Room2 | AP | 10.5 | 10.0~11.4 | 11.2 | 10.8~11.5 | 11.6 | 11.2~12.3 | ||
Room1 | AP | 12.5 | 8.9~17.4 | 13.9 | 12.0~16.4 | 14.4 | 14.1~14.7 | ||
PA | 9.9 | 9.4~12.4 | 12.8 | 12.4~13.0 | 14.3 | 14.2~14.4 | |||
Room2 | AP | 8.4 | 8.0~9.4 | 9.9 | 9.6~10.9 | 11.7 | 11.4~12.6 | ||
Room1 | AP | 13.4 | 10.8~17.7 | 14.0 | 12.6~16.1 | 14.6 | 14.3~15.0 | ||
PA | 11.8 | 11.4~12.2 | 13.2 | 12.9~13.5 | 14.5 | 14.4~14.6 | |||
Room2 | AP | 9.0 | 8.4~9.7 | 10.3 | 9.9~11.2 | 11.7 | 11.4~12.5 | ||
Hami | Room1 | AP | 14.6 | 11.3~19.5 | 16.3 | 14.0~18.9 | 16.5 | 16.2~16.9 | |
PA | 12.6 | 12.1~13.2 | 15.3 | 15.0~15.7 | 16.4 | 16.3~16.5 | |||
Room2 | AP | 10.1 | 9.7~11.0 | 11.4 | 11.1~12.2 | 12.0 | 11.7~12.8 | ||
Turpan | Room1 | AP | 13.7 | 9.6~18.6 | 14.6 | 12.4~17.3 | 14.9 | 14.4~15.4 | |
PA | 11.8 | 11.2~12.5 | 13.4 | 12.9~13.9 | 14.8 | 14.7~14.9 | |||
Room2 | AP | 10.3 | 9.6~11.0 | 11.1 | 10.6~11.9 | 11.8 | 11.5~12.5 | ||
Yining | Room1 | AP | 14.9 | 12.2~19.9 | 15.9 | 14.4~18.3 | 16.0 | 15.7~16.4 | |
PA | 13.1 | 12.6~13.7 | 15.1 | 14.8~15.6 | 15.9 | 15.8~16.0 | |||
Room2 | AP | 10.6 | 9.8~11.6 | 11.2 | 10.8~11.6 | 11.7 | 11.3~12.4 | ||
Ruoqiang | Room1 | AP | 14.8 | 13.2~21.7 | 16.2 | 14.3~18.7 | 16.4 | 16.1~16.9 | |
PA | 13.6 | 12.9~14.2 | 15.0 | 14.5~15.6 | 16.3 | 16.2~16.4 | |||
Room2 | AP | 10.6 | 10.1~11.4 | 11.3 | 10.7~11.9 | 12.4 | 12.1~13.1 | ||
Less |
Tongde | Room1 | AP | 11.5 | 8.3~16.1 | 12.1 | 10.5~14.5 | 12.7 | 12.4~13.1 |
PA | 9.6 | 8.9~10.3 | 11.0 | 10.6~11.8 | 12.6 | 12.5~12.7 | |||
Room2 | AP | 7.7 | 7.0~8.2 | 8.4 | 8.0~9.1 | 9.4 | 9.0~9.9 | ||
Madoi | Room1 | AP | 14.4 | 10.7~19.5 | 15.1 | 12.2~17.7 | 15.2 | 14.7~15.8 | |
PA | 12.0 | 11.2~12.7 | 14.2 | 13.8~14.7 | 15.1 | 15.0~15.2 | |||
Room2 | AP | 9.4 | 8.0~10.0 | 10.1 | 9.5~10.6 | 11.2 | 10.6~11.6 | ||
Altay | Room1 | AP | 9.0 | 6.8~12.5 | 11.5 | 10.2~13.2 | 12.3 | 12.0~12.7 | |
PA | 7.6 | 7.2~8.2 | 10.8 | 10.5~11.1 | 12.2 | 12.1~12.3 | |||
Room2 | AP | 7.0 | 6.5~7.9 | 7.8 | 7.3~8.6 | 8.9 | 8.5~9.7 | ||
Non- |
Room1 | AP | 6.8 | 4.7~10.8 | 8.6 | 7.4~10.2 | 9.3 | 9.0~9.8 | |
PA | 5.7 | 5.3~6.1 | 8.1 | 7.9~8.4 | 9.2 | 9.1~9.3 | |||
Room2 | AP | 4.2 | 3.6~5.1 | 5.2 | 4.7~6.1 | 6.4 | 6.1~7.2 | ||
Room1 | AP | 0.1 | –1.7~3.3 | 3.7 | 2.7~5.0 | 4.4 | 4.2~4.7 | ||
PA | –1.0 | –1.2~–0.8 | 3.2 | 3.0~3.4 | 4.3 | 4.2~4.4 | |||
Room2 | AP | –1.1 | –1.5~0 | –1.0 | –1.5~–0.8 | 0.5 | 0.2~0.8 |
Note: AP: 6:00 am to 10:00 pm, and PA: 10:00 pm to 6:00 am.
As shown in
Based on the above analysis, the suitability of passive solar heating technology in different regions of Northwest China was obtained. It can be learned that most regions in Northwest China are suitable for the development of passive solar heating technology. Moreover, over 70% of the regions in Northwest China comply with the following law: I-C is the most suitable region, II-Cold is the more suitable region, II-Severe Cold and III-Cold are the less suitable regions, and III-Severe Cold is the unsuitable region. However, this regularity is not apparent in certain regions of Xinjiang and Qinghai (italics in
This work took the rural dwellings in Northwest China as the research object. The current indoor and outdoor thermal environment in winter and the mechanism of residents’ differentiated demand for indoor thermal comfort were analyzed. On this basis, suitable differentiated indoor comfort temperature indexes and the passive optimized combination scheme for improving the indoor thermal environment were explored. Finally, the suitability of passive solar heating technology for each region of Northwest China was analyzed based on residents’ differentiated demand for indoor thermal comfort. The conclusions are summarized below:
In winter, the outdoor temperature was low and the temperature difference between day and night was large in the rural areas of Northwest China. Although the heating energy consumption was high, the indoor thermal environment was still not ideal. However, the area was rich in solar energy resources. It was proposed that during the activity period (from 6:00 am to 10:00 pm), the average indoor temperature of the main and secondary functional rooms should be at least 15°C and 12°C, respectively. During the sleep period (from 10:00 pm to 6:00 am the next day), the average indoor temperature of the main functional rooms should be at least 13°C. The indoor thermal environment of the buildings with optimized combination schemes was improved significantly. The average indoor temperature of the main and secondary functional rooms increased by at least 3.6°C and 4.0°C, respectively, and the temperature fluctuation decreased by at least 32.6% and 75.0%, respectively. The suitability of passive solar heating technology for each region of Northwest China was obtained. According to the suitability, the regions were classified into most suitable, more suitable, less suitable, and unsuitable regions.