An enthalpy-based energy savings estimation method targeting thermal comfort level in naturally ventilated buildings in hot-humid summer zones

Applied Energy 187 (2017) 717–731

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An enthalpy-based energy savings estimation method targeting thermal comfort level in naturally ventilated buildings in hot-humid summer zones Yueer He a,b,c,d, Meng Liu a,b,c,⇑, Thomas Kvan d, Shini Peng a,b a

Chongqing University, Chongqing 400044, PR China Key Laboratory of the Three Gorges Reservoir Region’s Eco-environment under MOE, Chongqing University, Chongqing 400044, PR China National Centre for International Research of Low-carbon and Green Buildings, Chongqing University, Chongqing 400044, PR China d The University of Melbourne, VIC 3010, Australia b c

h i g h l i g h t s
Energy saving potential is assessed by energy balance and thermal comfort.
Enthalpy change is used as the result of energy fluxes of a room in hot-humid zones.
Thermal comfort index APMV is proper for naturally ventilated buildings.
Steps are given to design a well-performed naturally ventilated building.

a r t i c l e

i n f o

Article history: Received 15 July 2016 Received in revised form 18 November 2016 Accepted 25 November 2016

Keywords: Total heat balance of a room The first law of thermodynamics Air enthalpy Thermal comfort Humidity issue

a b s t r a c t This paper examines naturally ventilated buildings in hot and humid summer zones and proposes an air enthalpy-based energy conservation rating method with an emphasis on the combined thermal comfortventilation parameters, particularly the impact of humidity and human adaptations on thermal comfort. The new method starts with energy flow analysis to a naturally ventilated room and assessment of thermal comfort accounting for the humidity of the naturally ventilated room as well as the occupants’ adaptability, differing from the PMV models and widely-used adaptive models adopted in existing rating methods. It contributes to designing a well-performed naturally ventilated building by analysing the interplay of climate elements, design features, indoor thermal comfort, and energy consumption for cooling in hot-humid climates. It also gives the access to rate the influence of an estimated energy saving due to natural ventilation on the energy system at a district or national scale. The proposed method is then applied to a naturally ventilated office located in three cities within this particular climatic region of China. The results indicate that natural ventilation is an effective way to improve thermal comfort while maintaining a low cooling energy consumption in hot-humid summer zones. Using natural ventilation could help reduce cooling energy demand by 10–30% compared to not using natural ventilation. Its energy saving potential is strongly affected by the enthalpy of outdoor air, followed by airflow rate. Then, a contrast comparison between the new method based on energy balance and Chinese indoor thermal comfort standard and the conventional method coupling adaptive ASHRAE standard-55 thermal comfort model with sensible heat balance model is carried out. The contrast results validate the considerable impacts of humidity on energy balance analysis and thermal comfort rating. It points out the new method makes improvement of the maximum energy saving potential of naturally ventilated buildings prediction. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction

⇑ Corresponding author at: 174, Shazheng Street, Chongqing 400044, PR China. E-mail address: [email protected] (M. Liu). http://dx.doi.org/10.1016/j.apenergy.2016.11.098 0306-2619/Ó 2016 Elsevier Ltd. All rights reserved.

Due to the poor quality of the thermal environment in hothumid climate zones, there is an increased demand for improvement of indoor thermal conditions [1]. Artificial cooling always

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results in increased energy usage and increased electricity cost to the occupants in a hot and humid climate [2,3]. Moreover, many studies reveal a statistically significant relationship in which buildings with air-conditioning, with or without humidification, are consistently associated with 30–200% higher incidences of sick building syndrome symptoms, compared to naturally ventilated buildings [4,5]. Considering such issues, natural ventilation in summer and transition seasons is a commonly used passive cooling technology to improve the indoor thermal comfort and air quality in such climate zones [6,7]. Determining whether natural ventilation would remain an acceptable means of indoor thermal comfort control requires prediction of the indoor conditions in the spaces when they are naturally ventilated. Consequently, the energy performance of natural ventilation should be assessed associated with the relation of climate, building design, and thermal comfort. A number of studies on cooling energy savings of using natural ventilation have considered the ventilation parameters, thermal comfort and energy savings together for various building types and climate zones [8–10]. Some research aimed at the natural ventilation performance of residential building designs by taking thermal comfort into account [11–14] while some were focused on hybrid ventilated buildings [15–17]. Some research discussed the link between the natural ventilation performance and urban environments [18]. Studies also covered various climates such as warm conditions [19], warm-humid conditions [20], and hot-dry summer climate [21–23]. Almost all of the aforementioned research took thermal comfort into account. The assessment of thermal comfort under naturally ventilated environment is mainly based on either PMV model [24–26] or adaptive models [27]. However, the PMV method, which is based on steady-state, human body heat balance theory [28] has been challenged by adaptive models [29]. The adaptive models adopted in existing methods are mainly based on four well-known and most widely accepted thermal comfort international standards: American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard-55 [30], the International Organization for Standardization (ISO) standard-7730 [31], the European standard EN15251 [32], and the Chartered Institution of Building Services Engineers(CIBSE) [33]. These international comfort standards are almost all based on North American and northern European subjects [31,34]. It has not been clarified in the aforementioned standards whether they are applicable to different environmental conditions [29]. Taking hot-humid summer zones of China as an example, studies broadly covering different types of buildings found that adaptive models adopted in aforementioned standards, such as the ASHRAE and ISO, are not suitable due to the different climatic characteristics, significant sensation variations and human adaptations in China [35–38]. These studies generally indicate that there are discrepancies between people’s real thermal sensation and the predicted thermal sensation, especially for naturally ventilated buildings. Taking into account factors such as climate, social, psychological and behavioural adaptations of these regions, studies have been conducted within the context of thermal comfort, and Adaptive Predicted Mean Vote (APMV) model for China conditions has been proposed [29,39–40]. According to the China ‘‘Standard of climatic regionalization for architecture (GB 50178)” [41], hot-humid zones in China refer to the hot summer and cold winter climate zone, and the hot summer and warm winter climate zone. In other words, it contains the Yangtze River basin and Southern coastal regions. These areas are of important to the development of China due to the growth in population and the economy [42]. Natural ventilation is highly recommended in hot-humid zones in China [43,44]. Therefore, the objective of this work was to review existing methods for rating energy saving using natural ventilation, and then propose a new

method to rate energy use in naturally ventilated buildings based on energy balance and thermal comfort in the hot-humid climate regions of China.

2. Rating energy savings with a consideration of thermal comfort using natural ventilation To improve the estimation of energy benefits when deploying natural ventilation to achieve thermal comfort in a hot and humid environment, it is crucial to use a robust heat transfer model with appropriate thermal comfort criteria. Energy embedded in the flowing material consists of internal energy, macroscopic kinetic energy, gravitational potential energy, and flow work. The internal energy and flow work embedded in the flowing material are regarded as ‘‘enthalpy” in thermodynamics because they depend on the thermal state of the flowing material. When analysing the heat transfer process of creating a thermal environment, the macroscopic kinetic energy and gravitational potential energy embodied in the air are not taken into consideration, and hence the value of enthalpy is the energy of air per unit mass. Among various thermodynamic parameters, ‘‘enthalpy” is the indicator used to analyse the energy balance of a room. Hence, thermal load changes including sensible heat changes and latent heat changes can be regarded as alterations of the air enthalpy in the room [45]. In other words, the total heat balance is expressed as enthalpy-based balance of a room. Homod et al. [25] proposed a control system by employing all factors affected by indoor air enthalpy to predict system deviations and generate control actions pertaining to mechanical ventilation time. Liu et al. [46] studied the control strategies at different conditions of indoor load, ventilation and indoor air temperature and humidity by analysing two control modes, enthalpy control and temperature control, in a hot and humid climate. In practice, most studies described above simplify the heat balance as sensible heat balance, using the indoor temperature change as the result of energy fluxes, such as the multi-zone thermal and airflow model [19,47–48], BIN method [49] and CDD method [10,50]. Those methods have widely been used for predicting the cooling energy savings of using natural ventilation, neglecting the influence of latent heat on the total energy load. For instance, Florides et al. [15] reported ventilation in summer results in a maximum reduction of annual cooling load of 7.7% when maintaining the house at 25 °C. Taleb [21] investigated the potential energy saving prospects of integrating natural ventilation with air conditioning systems into the residential buildings of Dubai through the use of computer simulation. In distinction to these, however, latent heat cannot be neglected in high-humidity zones. Shin and Do [51] examined a building’s cooling energy use as it is predicted with outdoor dry-bulb temperature versus outdoor enthalpy in a hot and humid climate. As a result, the comparison utilizing the enthalpy-based cooling degree-days method resulted in an error margin of approximately 2% less than that of the temperaturebased cooling degree days method. In short, the analysis of total heat balance of a room is necessary in hot and humid climate zones. Natural ventilation is an essential passive strategy to maintain indoor thermal comfort, therefore, the thermal comfort criteria is coupled to the existing energy-saving evaluation methods for using natural ventilation. As mentioned earlier, thermal comfort criteria can be classified into two categories: PMV model and adaptive models. PMV model [28] based on the human heat balance reveals a complex interaction of dry bulb temperature, mean radiant temperature, air velocity, relative humidity, clothing insulation and activity level. Although it is accepted as applicable to all conditions in occupied spaces [30,52–53], it has been very difficult

Y. He et al. / Applied Energy 187 (2017) 717–731

to meet the standard’s narrow definition of thermal comfort without such mechanical assistance, even in relatively mild climatic zones; and it ignores the psychological dimension of adaptation [54]. Indoor comfort temperatures in naturally ventilated buildings are strongly influenced by shifting thermal expectations resulting from a combination of higher levels of perceived control, and a greater diversity of thermal experiences in such buildings [54]. The predictions of PMV models are not accurate under freerunning environment, especially under the slight thermal environment [55]. Taking these into account, adaptive models have been set up for different countries or districts based on the field investigations [54,56–59]. An important factor in the adaptive process is the pattern of outside weather conditions and exposure to them. As described earlier, the adaptive models coupled into existing methods are mainly based on four most widely accepted thermal comfort international standards (ASHRAE standard-55, ISO standard7730, EN15251, and CIBSE). Those standards are almost all based on North American and northern European subjects and predict likely comfort temperature or its ranges from monthly mean outdoor temperatures. However, in hot and humid climates areas of China, factors such as the effect of air humidity and human adaptations on human sensation should be carefully considered [39]. It was found that the Chinese people have a broader range of tolerance to thermal stress, and very active in adapting the indoor thermal environment by behavioural adaptation, in particular those who live in hot and humid climate areas [29]. In hot and humid climates, it would be intuitive to hypothesize that humidity should play a dominant role in the human perception of thermal comfort and perceived air quality [60]. A climate chamber study involving 20 subjects in summer in China revealed that, for higher temperatures, relative humidity could play a significant role on skin temperature and thermal sensation [61]. Many findings indicate that relative humidity has different effects on human thermal sensation under different ambient temperatures and relative humidities, especially in free-running buildings, and that the effect of relative humidity on human thermal perception increases significantly when the ambient dry-bulb temperature is higher than 28 °C and relative humidity is higher than 70% [62–67]. Hence, taking the indoor temperature as the singular index is clearly insufficient for evaluating the indoor thermal comfort in such climate [68,69]. With the context of China, APMV model has been proposed [70] and adopted in the national ‘‘Evaluation standard for indoor thermal environment in civil buildings (GB/T50785-2012)” [40] to evaluate the indoor thermal environment. In summary, the adaptive model is more suitable for thermal comfort evaluation of naturally ventilated buildings compared to PMV model [54], and hence it has been coupled to the energy savings rating methods for natural ventilation. However, the widely used adaptive models based on international standards like ASHRAE and ISO ignore the great diversities of climatic characteristics and significant sensation variations and human adaptations in China. Hence, the existing methods may result in an inaccurate evaluation of natural ventilation use in such climate regions. Although significant studies on what the most adequate method to assess thermal comfort in naturally ventilated buildings in hot-humid climate zones of China is have been done, there is lack of study on coupling adequate adaptive thermal comfort model to quantify energy savings of naturally ventilated buildings in this particular climate zone. This work is to assess the energy savings of naturally ventilated buildings located in hot-humid climate zones in China while maintaining indoor thermal comfort. Due to the characteristics of naturally ventilated buildings, climate and human adaptations, the APMV model is adopted and the analysis of the total heat balance of a naturally ventilated room is conducted. Based on that, this paper also examines the new method

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integrating Chinese indoor thermal comfort standard with total heat balance model by comparing with the existing method coupling adaptive ASHRAE standard-55 thermal comfort model with sensible heat balance model.

3. Methodology The energy savings of a naturally ventilated room could be analysed by using the first law of thermodynamics and the following steps were used in the proposed method: (1) Identifying the thermodynamic system; (2) Analysing the energy flow to the system in regard to natural ventilation; (3) Building the energy balance model of the thermodynamic system; (4) Assessing the energy saving potential of natural ventilation targeting thermal comfort. Given those steps, this section consisted of two parts, namely analysing the energy balance of a naturally ventilated room and determining the energy saved by natural ventilation. 3.1. Energy balance of naturally ventilated rooms 3.1.1. Attributes of the thermodynamic system The first law of thermodynamics was applied here to set up the energy balance of a naturally ventilated room. The indoor air of the naturally ventilated room was considered as a thermodynamic system and the building envelope considered being the boundary of the system. 3.1.2. Energy flow to the thermodynamic system Energy flow to the thermodynamic system happens with indoor heat gain approaches, shown as Fig. 1, which result in the indoor thermal and humid environment. Increases in the sensible and latent heat of the indoor air arise from ‘‘external disturbances” and ‘‘interior disturbances.” External disturbances, primarily outdoor meteorological factors such air temperature, relative humidity, solar radiation, wind conditions of adjoining spaces, outdoor or in rooms, affect heat and moisture in the room by means of building envelope transfer, ventilation and infiltration. Interior disturbances are primarily due to appliances, lighting, and occupants. With regards to the thermodynamic system, energy flow to the naturally ventilated room was identified to comprise three parts: (1) that crossing the system boundary; (2) that due to the material flow, i. e. airflow, caused by ventilation and infiltration. For this paper, only the natural ventilation rate was considered. (3) that due to the heat and vapour dissipation of indoor objects, such as humans, lighting systems, and appliances. Given that, the following assumptions were made to analyse the effect of natural ventilation on cooling energy consumption: (1) The energy flow to the naturally ventilated room was conducted at each time interval. The length of each interval depends on specific situations. Here, the weather data were from the nearby meteorological station, recording data hourly. For this reason, the length of each interval was always set to one hour. (2) Energy gain from building envelope and indoor heats were totally absorbed by indoor air. (3) Inlet airflow was equal to outlet airflow.

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Fig. 1. Formation of a thermal, humid environment indoors.

(4) Indoor air was thoroughly mixed with the ventilation airflow, thus the internal temperature, humidity, and air pressure were assumed to be uniformly distributed. (5) The temperature difference among each internal surface including indoor heats were ignored. (6) Although the occupants’ behaviour is an unpredictable factor in all cases, it is assumed a known activity is undertaken in the room at a steady pace and that occupants utilise natural ventilation in the space. Based on these assumptions, energy flow to the naturally ventilated rooms was considered below. 3.1.2.1. Energy flow through the system boundary. Latent heat through the system boundary refers to the amount of moisture transferred through a building envelope due to the difference in water vapour pressure inside and outside the building envelope. The mass of latent heat gain through the building envelope was in this case very small compared to the moisture dissipation of indoor objects [71]. It was not taken into consideration in this section. Due to the different heat transfer processes, building envelop is classified as opaque and non-opaque parts. Each of these is considered in turn.


@tðx; sÞ

¼0 @x
x¼0 h½tðd; sÞ  t 1  ¼ k

ð3Þ
@tðx; sÞ

@x
x¼d

In this model, based on the Harmonic reflection method, the idea of ‘‘Equivalent cooling load temperature difference” was adopted [72]. The simplified calculated was shown as Eq. (5):

Q Es;s ¼ 3:6

n X K w;j F j ðt out;se  tin;s Þ ðkJ=hÞ

ð5Þ

j¼1

Here, s-e reflects the decay rate and time lag of heat conduction of building envelope, which is determined by its thermal inertia. (2) Energy flow through the glazing This consists of two parts: heat conduction and the solar heat gain through the glass. Heat conduction through the glass can be regarded as steady-state heat transfer determined by the thermal properties of the glass. Thus, the mass of heat conduction can be calculated using Eq. (6) on the basis of steady-state heat transfer theory: m X Q Gs;s ¼ 3:6 ak K g;K F g;K ðtout;s  tin;s Þ ðkJ=hÞ

(1) Energy flow through the opaque building envelope

ð4Þ

ð6Þ

k¼1

According to the assumptions descried earlier, heat gain through building envelope here is determined by the temperature difference between inside and outside air. Temperature fluctuations on the inside surface of a non-transparent building envelope are related to the thermal performance of the building envelope and the thermal load (including insolation) on the exterior skin. Based on the knowledge of heat transfer, heat transfer through the opaque building envelope can be considered as Onedimensional unsteady heat conduction model. Solutions for the heat transfer process were as follows:

Solar heat gain through the glass includes direct sun penetration and the heat that is first absorbed by the glass and then transferred into the room by means of convection and radiation. In this way, the heating of the glass by solar radiation, coefficient of solar heat gain, and impact of the shading must be taken into account. The heat flow through the glass and the solar radiation on the glass can be calculated using Eqs. (7) and (8) [73], respectively.

Q GIs;s ¼ 3:6

m X ak Ik;s F g;K SC;k ðkJ=hÞ

ð7Þ

k¼1

@t @2t ¼ a 2 ð0 < x < d; s > 0Þ @s @x

ð1Þ

Ik;s ¼ Idir;k;s  gk;s h þ ðIdif;k;s þ Iref;k;s Þgk;s ð45 Þ

tðx; 0Þ ¼ t0 ð0 6 x  dÞ

ð2Þ

Eq. (8) was calculated by considering the angle of solar incident [74–77]. Given a solar incident angle h, the solar heat gain

ð8Þ

Y. He et al. / Applied Energy 187 (2017) 717–731

coefficient with h and the solar heat gain at the calculation moment were obtained in terms of the building’s location. The optical properties of glass have been studied as well. Karlsson and Roos [78] investigated the solar heat gain coefficient g of glass of different thicknesses and layers, and reported that the main factors affecting the solar heat gain coefficient g were the type of coating and the number of panes; the thickness of the coating, the absorption and the thickness of glass are of less importance. Possible ways to simulate the solar heat gain coefficient g were also reviewed in their research. When the value of g was not provided in the product information, the polynomial model was used to determine it [74]. 3.1.2.2. Energy flow due to the material flow. As noted earlier, the macroscopic kinetic energy and gravitational potential energy embodied in the air were not taken into consideration. The value of enthalpy is here the energy of air per unit mass, which can be calculated using Eq. (9). The air discussed here refer to the moist air, and the enthalpy of air per unit mass was determined on the basis of one kilo of dry air. Here, the mass of moist air was calculated by using Eqs. (10) and (11). Eq. (11) was generated by Magnus [79], and the coefficients were as follows: T0 = 273.16 K, E0 = 6.11 hPa, a = 6764.9 K, b = 4.9283.

h ¼ 1:01t þ 0:001dð2501 þ 1:85tÞ ðkJ=kgðaÞÞ

ð9Þ

721

tall) produce large-scale turbulence that not only reduces effective wind speed but also alters wind direction, especially for relatively short buildings. Because of this, the idea of modifying the Umet from a nearby meteorological station to identify the wind speed profile works as follows: The atmospheric boundary layer thickness, exponent for the local building terrain and the shelter factor for the particular wind direction are identified based on the building conditions, which could present the impact of surroundings on the wind conditions. 3.1.2.3. Energy flow due to the heat and vapour dissipation of indoor objects. Indoor heat and humidity sources mainly contain occupants, appliances, and lighting systems. Sensible heat from the lighting and appliances can be estimated on the basis of the lighting power density and power budget of electrical appliance given by the energy saving standard (Eqs. (13) and (14)). The sensible and latent heat due to occupants is related to their metabolic rates. These depend mainly on their exertion, which means the total heat from occupants can be approximately considered as a constant when the intensity of activity is constant. The sensible and latent load due to occupants can be calculated using Eqs. (15) and (16).

Q Li;s ¼ 3:6qLi AwLi;s ðkJ=hÞ

ð13Þ

Q Eq;s ¼ 3:6qEq AwEq;s ðkJ=hÞ

ð14Þ

m ¼ ðB  Pv ÞV=287T ðkgðaÞ=sÞ

ð10Þ

Q PS;s ¼ 3:6cqs PAwP;s ðkJ=hÞ

ð15Þ

PV ¼ uPS ¼ uE0 ðT o =TÞb expða=T o  a=TÞ ðPaÞ

ð11Þ

Q PL;s ¼ 3:6cqL PAwP;s ðkJ=hÞ

ð16Þ

V in Eq. (10) represents the volume flow rate due to natural ventilation, understood to be the flow of outdoor air caused by wind and thermal pressures through intentional openings in the building’s shell. The volume flow rate due to natural ventilation can be calculated by Eq. (12) [80].

V ¼ CD Fg

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2C P U 2 =2 þ 2ðT in  T out ÞgðHNPL  Hw Þ=T i ðm3 =sÞ

ð12Þ

The discharge coefficient CD in Eq. (12) is for the opening accounts for all viscous effects such as surface drag and interfacial mixing [9]. The surface-averaged pressure coefficient CP is a key driving force due to wind pressure. The value of CP depends on wind direction, the geometric construction of building, opening size and surroundings. CP is almost independent of wind speed for a building with sharp comers because the flow separation points normally occurs at the sharp edges [81]. In other words, the change in any of these parameters but wind speed could in turn change the value of CP considerably. Accurate data for CP can only be obtained using fullscale measurement or wind tunnel experiments. At present, many wind load codes (e.g., ASCE Standard ASCE/SEI 7-10, SA/SNZ Standard AS/NZS 1170.2) give mean pressure coefficients for buildings with common shapes. The method of calculating CP in this paper is from the ASHRAE Handbooks of Fundamentals. Estimation of height of neutral pressure level (NPL) is difficult for naturally ventilated buildings, which should be analysed by taking the specific building information into account. The NPL in tall buildings usually varies from 0.3 to 0.7 of total building height [82]. In addition, the local wind speed U that is required for Eq. (12) must be estimated using terrain and height corrections to the hourly wind speed Umet from a nearby meteorological station. This is because conditions for a real project are different from those measured at the meteorological station, affected by factors such as the building height and attributes of underlying surfaces. The shielding effects of trees, shrubbery, and other buildings near the target (no more than several times as far away as the building is

3.1.3. Energy balance of the thermodynamic system Based on the basic theory of the first law of thermodynamics and the analysis of the energy flow to the thermodynamic system, the energy balance equation for the thermodynamic system accounting for sensible heat and latent heat can be established as Eq. (17).

3600m1;s h1;s þ Q Es;s þ Q Gs;s þ Q GIs;s þ Q Li;s þ Q Eq;s þ Q Ps;s þ Q PL;s  3600m2;sþds h2;sþds ¼ DQ ds

ð17Þ

Eq. (17) shows energy balance per interval of the naturally ventilated room. The indoor air enthalpy is taken as the result of the balance of energy fluxes. The amount of energy flowed into the thermodynamic system per interval contains energy stored in the natural ventilation airflow (m1,sh1,s), energy gain through the building envelope (QE-S,s for the opaque building envelope, QG-S,s and QGIS,s for the transparent part) and energy gain due to internal heats. The energy expenditure of the system is due to outlet airflow (m2, s+dsh2,s+ds). The item on the right hand side stands for the heat gain of the free-running room. Based on the law of conservation and transformation of energy, the left hand side of Eq. (17) is equal to its right hand side. Based on the energy balance equation of the naturally ventilated room, the input data, output data and the manner in which these kinds of data can be assessed layer by layer are shown in Appendix A. Arguments related to Level II are used to identify arguments related to Level I. As shown in Appendix A, there are three approaches for collecting input data, which are weather conditions, basic information of building design, and empirical formulas. Meanwhile, solution parameters for the model include values of temperature, humidity, and vapour pressure at time s and time s + ds. The solution for this model is found iteratively, which means the algorithm requires the output data from the preceding interval. In this model, the hygrothermal status of the indoor air is assumed as the same as that of the outdoor air at the first interval.

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3.2. Method of determining the amount of energy saved by using natural ventilation 3.2.1. Thermal comfort assessment for naturally ventilated spaces under a hot and humid climate Considering the limitations of using the PMV model and adaptive models based on ASHRAE standard-55, ISO standard-7730, EN15251 and CIBSE in hot and humid climate zones in China, APMV model was used to evaluate the indoor thermal comfort of naturally ventilated rooms. As one of the outputs of energy flow model, APMV for every interval was calculated. Table 1 showed the details about the APMV assessment. Here, APMV for 1 till 1 is acceptable in the Standard [40].

3.2.2. Quantifying the energy saving potential of natural ventilation The cooling electricity consumption with natural ventilation ENV can be estimated on the basis of the energy balance equation (Eq. (17)).

ENV ¼

n X dsi DQ si =3600COP ðKWh=aÞ

ð18Þ

i¼1

 d si ¼

1; if APMV si > 1 and DQ si > 0: 0;

if APMV si 6 1 or DQ si 6 0

ð19Þ

where dsi is the condition for energy savings estimation, i and n refer to the ith time interval and the amount of intervals. Taking the minimum allowable values of the energy efficiency for variable speed room air conditioners, the COP here was assumed as 3 [83]. Rated by the APMV model, the indoor thermal environment with natural ventilation could be classified into three cases. Case I is acceptable with APMV for 1 till 1. Case II is a chill or cold thermal environment when APMV is below 1. In Case II, heating might be needed. Case III is a warm or hot thermal environment when APMV is above 1. Case III happens when energy flow due to natural ventilation is unable to remove the indoor heat gain from the building envelop and indoor objects; or when the outdoor weather is hot, natural ventilation results in more heat gain compared to not using natural ventilation. In Case III, mechanical cooling may be needed. Natural ventilation is a commonly used passive cooling technology [6]. Consequently, this work is focused on the effect of natural ventilation on cooling loads in hot and humid summer zone. Hence, the possible energy consumption for cooling is included while the energy consumption for heating is excluded when determining the energy savings of a naturally ventilated room. To rate the energy benefits of natural ventilation for a whole year, relative energy savings ratio RE is defined as:

RE ¼ ðEAC  ENV Þ=EAC ð%Þ:

ð20Þ

where EAC stands for the cooling energy consumption with airconditioning only.

Table 1 Overall evaluation indexes. Category

APMV

Meaning

I

0.5 6 APMV 6 0.5

II

1 6 APMV < 0.5 or 0.5 < APMV 6 1 APMV < 1 or APMV > 1

More than 90% of people are satisfied with the thermal environment More than 75% of people are satisfied with the thermal environment Fewer than 75% of people are satisfied with the thermal environment

III

3.3. The functions of the new method and its applications in practice The rating method presented in this work provides an approach to analyse the interplay of hot-humid climate elements, design features, indoor thermal comfort, and building energy consumption for cooling. Basically, the model can be used to evaluate the indoor hygrothermal environment level of a naturally ventilated room located in hot-humid climate zones and its energy efficiency by quantifying energy flow to the room. Furthermore, it contributes to optimizing the natural passive ventilation design. As noted earlier, the free-running room was treated as a thermodynamic system, energy flow to the room was identified to comprise three parts. Among those three parts, energy flow through the system boundary and energy flow due to the material flow were closely related to the characteristics of architectural design. From the architectural expression view, relevant factors required in the model were re-summarized in Table 2. Those required inputs involve the selections of building materials, shadings, building forms and orientation, window design and surrounding conditions. Those design features affect the performance of natural ventilation in solar radiation control and ventilation airflow rate, and hence modifies the heat flow to the interior. For instance, ventilation problems associated with the relation between the direction of the prevailing winds and the orientation of the building, shading effects, window size, etc. [84]. Or heat transfer through the building envelope varies under different outdoor climate conditions and the thermal performance of the building envelope (e.g. the K-value, the heat-storing capacity, windowwall ratio, shading, and selections of different types of glass layers, special gas gaps, and coating). The changes of each parameter directly affect the result of the evaluation, introducing the uncertainties of the use of natural ventilation. The optimal combination and relative importance of inputs varies under different climatic conditions and in various situations. The proposed method give an approach to design a wellperformed naturally ventilated room and rate its energy efficiency, which can be divided into three steps. The first step is to analyse climatic elements at a given location, such as temperature, relative humidity, radiation, and wind effects. The yearly/monthly/hourly characteristics of these elements should be analysed. And the modified effects of the microclimatic conditions should be considered. The requirements of indoor thermal environment response to the climate need to be recognized. The second step is to evaluate the climate impact in physiological terms. The climate data is expected to be adapted to the thermal comfort requirements. If not, climate comfort problems should be recognized. In this work, the focus is given to cooling effects of using natural ventilation. The times when naturally ventilation Table 2 The relation between architectural design and energy flow. Energy flow

Architectural expression

Inputs

Through system boundaries

Orientation Building envelope

– Opaque parts Glazing Window: wall ratio Shading devices

I Kw, s-e Kg; g(h) F; Fg Sc

Due to material flow

Orientation Surroundings

– Attributes of underlying surfaces

Window design

Layout Size Shading effects

CP Correction factors for wind speed from a nearby meteorological station CP; HNPL Fg CD

Y. He et al. / Applied Energy 187 (2017) 717–731

might be considerable are determined by rating the outdoor climate using the APMV model. The third step is to decide the suitable characteristics of architecture design. With Eqs. (5)–(20), the improvement of indoor thermal environment and energy savings of each naturally cooling design strategy will be quantified. The best design at a given location could be decided. 4. Case study 4.1. Case conditions To discuss the energy saving potential of natural ventilation by using the proposed energy flow model and evaluation method, three typical cities within these area of China, namely Chongqing (E106°450 , N30°), Changsha (E113, N28°110 ) and Guangzhou (E113°30 , N23°20 ), were selected to do the further case study. A two-level free-running office building was set out in each of the city and occupied from 8:00 a.m. to 6:00 p.m. 4.1.1. Climate conditions Meteorological data for each city were obtained from ‘‘Meteorological data set for the building thermal environment analysis in China”. Their prevailing wind direction is northwest and the wind speed is almost less than 5 m/s all the year around. Fig. 2 and Fig. 3 showed the average monthly dry bulb temperature and average monthly relative humidity of each city. It can be seen that Guangzhou got the highest temperature in each month, followed by Chongqing, Changsha. On the other hand, the relative humidity in Guangzhou is lower than other two cities. The APMVs under the outdoor climate for each city were calculated and shown as Fig. 4. Based on the requirements of Category I and II proposed in Standard GB/T50785-2012, the ratios of outdoor climate conditions met comfort requirements, was shown as Fig. 5. It can be seen from Fig. 5, the comfortable hours’ ratios in transition seasons is much higher than those in other seasons. The suitable period for using natural ventilation in Guangzhou (March till December) is longer than other two cities (April till November, plus part time in March). According to the outdoor climate conditions, the suitable period from March to November was defined to use natural ventilation. The energy benefits of natural ventilation in this period for each city were discussed.

723

façade. Fig. 6 is the plan of level 2 of the subject building, indicating the location of the case room. The design characteristics of this building, as assessed using the requirements of local energysaving code,” is summarized in Table 3. The proposed method with Eq. (5)–(20) was used in this specific case. The case room was monitored from March to November in each city and the indoor temperature and humidity observed to improve due to natural ventilation. According to the case conditions, all the input data for the energy flow analysis were identified based on the hourly climate data of each city. The identification of several key input data, namely solar heat gain coefficient g, wind pressure coefficient CP and wind speed modification, were interpreted as follows: (1) Identifying the value of solar heat gain coefficient g in Eq. (8) The value of g was crucial to calculation of solar heat gain, which was discussed in Section 3.1.2.1. Here, the calculation method used for g was provided by the production information (shown in Table 3). (2) Determining the wind pressure coefficient The hourly average values of wind pressure coefficient CP were calculated based on the building design features and hourly meteorological data of each city. (3) Modifying wind speed According to the analysis in Section 3.1.2.2, the wind speeds obtained from the meteorological data were modified based on the case conditions. Considering the terrain attributes (urban, average height of local obstacles, space between buildings), shelter attributes, the height of the room model, a boundary layer thickness of 370, an exponent of 0.22, and a shelter factor of 0.3 were chosen [80]. After identifying input data, energy flow to the naturally ventilated room in each city was analysed. From the energy balance Eq. (17), two key factors of quantifying energy performance of natural ventilation were obtained, namely the cooling load DQ of the naturally ventilated room and the value of APMV in each interval. This being the case, the energy performance of natural ventilation was rated on the basis of the rating method presented in Section 3.2. 4.2. Results and discussion

4.1.2. Building’s information In order to improve natural ventilation, the room model is oriented northwest with the operable window on the northwest

Using the air enthalpy-based energy savings estimation method, the performance of natural ventilation from March to

Fig. 2. The average monthly dry bulb temperature of each city.

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Fig. 3. The average monthly relative humidity of each city.

Fig. 4. APMVs under outdoor climate conditions during work hours in the typical year of each city.

Fig. 5. Comfortable hours’ ratio under outdoor climate in the typical year of each city.

November for each city was obtained. Fig. 7 illustrated the monthly RE ratios for each city by using natural ventilation during working hours; Fig. 8 showed the ratio of comfortable indoor thermal environment hours to whole working hours. Overall, energy saving potential of natural ventilation in Changsha was the best of the three cities. RE ratio of Changsha for the typical year was 31.6%, followed by Chongqing (23.3%) and Guangzhou (10.4%). In terms of the ability of natural ventilation to improve the thermal environment, Chongqing was the best of

all, the ratio of comfortable hours with natural ventilation of which was 46%; followed by Guangzhou (43%) and Changsha (38%). The different orders of RE ratios and comfortable indoor hours’ ratios were due to the definition of the RE ratio. According to the outdoor climate conditions, the period from March to November was determined to use natural ventilation. The ratio of uncomfortable hours with natural ventilation of each city was shown in Fig. 9. Uncomfortable periods might be the cool or cold thermal environment requiring heating and/or warm or hot thermal environment

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Fig. 6. Plan of level 2 of the office building.

Table 3 Key characteristics of case building. Building design Building size Orientation Materials

Window: wall ratio

Two levels, total floor area of 200 m2 Northwest Concrete shear wall (k = 0.77 w/m2 k, e = 7 h) Overhead roof (k = 0.60 w/m2 k, e = 12 h) Single glazing (thickness: 5 mm, k = 2.5 w/m2 k g(h) = 1  8(h/90)8  1/16 (h/90)2 + 113/ 16 (h/90)8.4) 40% (Same for every room.)

Room model Building dimensions Window opening size Window operable area Opening shape Opening orientation Window opening schedule Shading

3.2 m (length)  2.5 m (width)  2.8 m (height) 3.6 m2 (it is designed by the local energy code) 1.66 m2 2.4 m (length)  1.5 m (height) Northwest Kept open during working hours None

Indoor load Number of occupants Schedule of occupants Lighting power density Using of lighting Power budget of electric devices Hourly capacity utilization

Based on the energy-saving code

requiring cooling. From Fig. 9, the ratio of Changsha when APMV was below 1 was higher than the ratios of Chongqing and Guangzhou. But, energy consumption for heating needed in times when APMV was below 1 was excluded when calculating the RE ratio in this study, which had been explained in Section 3.2.2. This being the case, the ratio of comfortable hours with natural ventilation of Changsha was the lowest in the period from March to November, it could still have the best cooling energy saving potential of natural ventilation. The energy saving potential of natural ventilation was different in each season, which had good accordance with the outdoor

climate conditions in each season (Fig. 5). Taking the RE ratio as the index, the performance of natural ventilation in transition season was the best while it performed the worst in summer. There were negative values sometimes in summer. This is because when the outdoor weather is hot, natural ventilation results in more heat gain compared to heat gain due to the minimum ventilation rate required in air-conditioning systems. As a result, cooling load with natural ventilation is higher than that with air-conditioning system. In March, April, October and November, the comfortable hour’s ratios with natural ventilation for both Chongqing and Changsha were lower than ratios in other months, while the RE ratios in those four months were significantly higher than others’. This is because the thermal sensation of the uncomfortable hours in these four months was cool or cold (refer to Fig. 9). The ratios of APMV < 1 for Chongqing and Changsha were 92% and 100%, respectively, which meant heating was needed instead of cooling. As noted earlier, energy consumption for heating was excluded. Hence, the high RE ratios (even 100%) were obtained while the comfortable hour’s ratios were low. In October, although the comfortable hours’ ratio of Guangzhou was the highest of the three cities, RE ratio of Guangzhou was lower than other two cities. This is because the outdoor climate conditions are hot in Guangzhou. Even in October, cooling was still needed because 3% of the working hours were in a hot indoor thermal environment. In May and June, the comfortable hours’ ratio with natural ventilation of Changsha was lower than that of Chongqing, while the RE ratio for Changsha was higher. In terms of outdoor climate conditions in May, the average outdoor air enthalpy in Chongqing is higher compared to Changsha. By using natural ventilation, 2% of working hours were still in hot thermal environment (APMV > 1) and air-conditioning cooling was needed. For Changsha, all the uncomfortable hours were in the cool thermal environment (APMV < 1), which meant no cooling demand. In June, the uncomfortable hours for both cities were in hot thermal environment (APMV > 1). But the average natural ventilation airflow in Changsha was higher than Chongqing. The indoor sensible and latent heat removed by natural ventilation in Changsha was more than that in Chongqing. The contrast results showed the performance of natural ventilation was affected most by the outdoor climate conditions, especially the outdoor air enthalpy, and then followed by the airflow rate.

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Fig. 7. Monthly relative energy savings ratios for each city.

Fig. 8. The ratio of comfortable indoor thermal environment hours to whole working hours.

Fig. 9. The ratio of uncomfortable hours with natural ventilation.

5. Compared to the conventional rating model A contrast comparison was carried out in order to investigate the distinction between the new method which integrates Chinese indoor thermal comfort standard with total heat balance model and the common used method which couples adaptive ASHRAE standard-55 thermal comfort and sensible heat balance model. The common used method has been integrated into the EnergyPlus simulation tool [12]. By using EnergyPlus, energy saving potential of natural ventilation for each city in the typical year can be obtained as well. The modelled results were shown as Fig. 10.

The general trends of two kinds of results were similar to a certain extent. Changsha got the greatest energy potential of using natural ventilation (4.8%) in the typical year, followed by Chongqing (4.2%) and Guangzhou (2.8%). The energy benefits of natural ventilation were much better in transition seasons compared to other months. There were negative values of RE ratios in summer. Looking at the thermal performance of natural ventilation, Chongqing was still the best of all, the ratio of comfortable hours with natural ventilation of which was 37.7%; followed by Changsha (36%) and Guangzhou (18%). The differences between the two methods were summarised as follows:

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Fig. 10. Monthly relative energy savings ratios for each city by using the conventional method.

(1) The percentage of acceptable comfort hours predicted by the new method was more than that predicted by the temperature-based method; (2) The RE ratios calculated by the new method were significantly higher than the RE ratios of temperature-based method; (3) In terms of the temperature-based method: in March, April, October and November, the RE ratios were not 100%, even dropped to zero; in transition seasons, RE ratios in Guangzhou were higher than RE ratios in other two cities; in June and September, the difference of RE ratios for Chongqing and Changsha was bigger than the difference obtained by the enthalpy-based method. According to ASHRAE 55, indoor operative temperature (TOT) is a function of indoor temperature and acceptable operative temperature ranges for naturally conditioned spaces are related to the mean monthly outdoor air temperature [30]. One might first use a building simulation tool to predict what indoor conditions might be achieved. In other words, the heat balance analysis will direct affect the results of indoor conditions prediction. To study the effects of humidity and latent heat on thermal comfort and room loads, respectively, Fig. 11 showed the indoor operative temperature results calculated by using the conventional method and the proposed method. The energy balance of the indoor air in conventional method is simplified to sensible heat balance ignoring the influence of natural ventilation on the latent heat and indoor temperature is taken as the result of the balance of energy fluxes, which result in the higher calculated indoor operative temperature (TOT) compared to real values. The acceptable periods of using natural ventilation will be decreased. As a result, RE ratios calculated by the temperaturebased method were much lower than the results of the enthalpybased method. For the same reason, several cases that still need air-conditioning were predicted even in March, April, October

and November. Consequently, the RE ratios in those months may drop to zero. Choosing Adaptive model as the thermal comfort criteria, the results of energy savings of using natural ventilation also illustrated the good accordance with the outdoor dry bulb temperature. When the outdoor temperature is below the acceptable operative temperature, energy savings will increase with the rising of the outdoor temperature. Hence, in March, April, May, October and November, the energy potential of using natural ventilation in Guangzhou was much better than the energy benefits of using natural ventilation in Chongqing and Changsha. Based on the conventional method, the RE ratio of Changsha in June was much higher than that in Chongqing (>12%). According to the proposed method, the difference for the two cities was only 3%. For Changsha and Chongqing, solar radiation and outdoor dry bulb temperature in June are almost the same. The average natural ventilation in Changsha is higher than that in Chongqing (>2%). The average enthalpy of outdoor air in Changsha is higher than Chongqing (>2%). By analysing the heat gain of the naturally ventilated room and the energy performance of using natural ventilation with different methods, it can be summarised that: natural ventilation airflow has effects on the energy performance of using natural ventilation; the lower enthalpy of outdoor air, however, has a greater capacity for removing the sensible and latent heat of indoor air, which makes up the lack of ventilation airflow. Hence, taking indoor air enthalpy as the results of energy fluxes is important to estimate the energy saving potential of using natural ventilation. The contrast results of two methods illustrated the correction of the proposed method and the air enthalpy-based method gives more accurate estimates of energy benefits of using natural ventilation. The adaptive model predicting comfort temperatures or its ranges from monthly mean outdoor temperatures cannot exactly forecast the thermal conditions of naturally ventilated buildings, especially in hot and humid climate. The thermal comfort is found to be significantly affected by the indoor air enthalpy.

Fig. 11. The contrast results of indoor operative temperature.

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Table A.1 Analysis of input/output data for the model. Input data

Sources of data

I

II

m1,s/m2, s+ds

B PV-out,s tout,s uout,s Vs

III

CD Fglass CP U

IV

V

dmet d Hmet H amet a S

tout,s tin,s HNPL Hw min, s

h1,s h2, s+ds hin,s QE-S,s

QG-S,s

QGI-S,s

B PV-in,s tin,s uin,s Vin tout,s dout,s tin,s+ds din,s+ds tin,s din,s Kw Fw tout,s-e tin,s a Kg Fg tout,s tin,s a Fglass SC Is

Vroom

gs(h)

h

u d

Climate data Climate data Climate data Climate data Building design information Building design information Building conditions + empirical Climate data Building conditions + empirical Climate data Building conditions + empirical Climate data Building conditions + empirical Building conditions + empirical Climate data Model calculations Building conditions + empirical Building design information Climate data Model calculations Model calculations Model calculations Building design information Climate data Climate data Model calculations Model calculations Model calculations Model calculations Building design information Building design information Climate data Model calculations Building design information Building design information Building design information Climate data Model calculations Building design information Building design information Building design information Building conditions + empirical

formula formula formula formula formula

formula

formula

x HS L LS e n

e Idir,s Idif,s Iref,s QLi,s

QEq,s

Qp-s,s

Qp-l,s

qLi wLi,s A qEq wEq,s A qs P wP,s A c qL P wP,s A c

I0 P m h

c a Building conditions + empirical formula + Climate data

Building design information

Y. He et al. / Applied Energy 187 (2017) 717–731

6. Conclusions Considering the climate features of hot-humid zones, the distinctions of thermal comfort assessment between naturally ventilated buildings and air-conditioning buildings and also between China and North American and northern European subjects, a new approach with Eqs. (5)–(20) could be used to determine energy savings in naturally ventilated buildings in hot-humid summer zones like Yangzi River Basin and Southern coastal regions of China. It provides an approach to analyse the interplay of climate elements, natural passive ventilation design, indoor thermal comfort, and energy consumption for cooling in a hot-humid climate. The required inputs to the model are key impact factors related to the natural forces and characteristics of building design. Following three steps advised in this work, the raise of thermal comfort level, optimum energy usage and psychological acceptance of occupants could be achieved. The application of this approach was exemplified by case studies in three cities within such climate zones of China. The results showed that using natural ventilation could help reduce cooling electricity energy by 10–30% compared to not using natural ventilation. The difference of cooling energy savings in specific location and in each season also indicates that energy saving potential of natural ventilation is strongly affected by the outdoor air enthalpy and then followed by the airflow rate resulting from the local climate and building design. When the performance of natural ventilation evaluated by the new method coupling enthalpy-based heat balance with Chinese indoor thermal comfort standard were compared with the results of the conventional model of which the methodology is temperature-based for both heat balance analysis and thermal comfort assessment, it could be found that: The predicted energy savings due to natural ventilation using the present model showed a reasonable accordance with those measured by the conventional model. On the other hand, the energy savings rated by the new method were significantly higher than those rated by the conventional model (The energy savings for the selected cities using the conventional model were 2–5%). The percentages of acceptable comfort hours predicted by the new method were higher than that predicted by the temperature-based method. The thermal comfort is found to be significantly affected by the indoor air enthalpy. The choice of thermal comfort criterion will then significantly affect the use of natural ventilation. The thermal comfort criteria for naturally ventilated spaces must pay attention to the climate characteristics and human adaptations of different areas. The new method makes improvement of the maximum energy saving potential of naturally ventilated buildings prediction in such climate zones. By solve the exiting issues in the energy saving potential rating of naturally ventilated buildings, the new method also contributes to assessing the influence of an estimated energy saving due to natural ventilation on the energy system at a district or national scale, which is the future work the authors would like to investigate.

Appendix B See Table B.1.

Table B.1 Nomenclature. ak a/amet A B c CD CP d e Fj Fg,k gk,s(h) h h1,s h2,s+ds hin,s HS H/Hmet HNPL Ik,s Idir,k, s Idif,k,s Iref,k,s K L LS m1,s m2,s+ds min,s n P PV qs qL QE-s,s QG-s,s QGI-s,s QLi,s QEq,s QP,s S Sc,k tout tin U Umet V W s-e h i

Acknowledgments

e u

x

This work was supported by the China NSFC International Cooperation Program [grant numbers 51561135002].

d

a c / d/dmet

Appendix A See Table A.1.

729

DQ APMV

The correction factor for the window frame on the kth building façade The exponent of building conditions and the meteorological station conditions. Floor space (m2) Local atmospheric pressure Percentage of men women and children Discharge coefficient Surface-averaged pressure coefficient Humidity ratio Jet lag Area of wall (m2) Size of the openings (m2) Solar heat gain coefficient at time s with the solar incident angle h Solar height angle Enthalpy of ventilation airflow at time s (kJ/kg) Enthalpy of mixed indoor air at time s + ds (kJ/kg) Enthalpy of indoor air at time s (kJ/kg) The local standard time Height of window on the buildings and the height of the meteorological station, respectively. Height of neutral pressure level (m) Solar gain through the window per interval (W/m2) Direct solar radiation on the window at time s (W/m2) Diffuse solar radiation on the window at time s (W/m2) Surface reflective radiation on the window at time s (W/m2) Thermal conductivity of building envelop (W/(m K)) Local longitude Latitudes of the location of the local standard time Dry-air mass of ventilation airflow at time s (kg(a)) Fry-air mass of exhaust air at time s + ds (kg(a)) Mass of indoor air at time s (kg(a)) Sequence number of the calculation day in the whole year Occupant density (m2/capita) Water vapour pressure (Pa) Sensible heat load of people (W) Latent heat load of people (W) Heat gain through non-transparent building envelop at time s (w) Mass of heat conduction by the glass at time s (w) Solar heat gain through the glass at time s (w) Heat load from the lighting at time s (w) Heat load from electrical appliance at time s (w) Heat and humidity load of human at time s (w) Shading factor Shading coefficient Temperature of outside air (°C) Temperature of indoor air (°C) The wind speed (m/s) Hourly wind speed from a nearby meteorological station (m/s) Volume ventilation flow rate (m3/s) Schedules of indoor objects Time of the outside heat and humidity loads acting on the exterior wall surface (h) Solar incident angle The angle of the building façade to the ground Sun azimuth on the building façade Local latitudes Solar hour angle Declination angle Sun azimuth Azimuth of the building façade Relative humidity (%) Boundary layer thickness for building conditions and the meteorological station conditions, respectively. The heat gain of the free-running room in every interval Adaptive predicted mean vote

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