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BIM-based framework to analyze the effect of natural ventilation on thermal comfort and energy performance in buildings
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10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China(ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China 15th International Symposium Districtof Heating and ventilation Cooling BIM-basedTheframework to analyze theoneffect natural on BIM-based framework to analyze the effect of natural ventilation on thermalthe comfort and energy performance in buildings Assessing feasibility of using the heat demand-outdoor thermal comfort and energy performance in buildings
a temperature forDeng a long-term heatC.P. demand Vincent function J.L. Gana, M. , Y. Tana, W.district Chena, Jack Chenga,*forecast a Vincent J.L. Gana, aM. Denga, Y. Tana, W. Chen , Jack C.P.c Chenga,* a,b,cof Civil and Environmental a b Univeristy of Science and Department Engineering, The Hong Kong I. Andrić *, A. Pina ,Clear P. Ferrão , J. Fournier ., B. Lacarrière , Technology, O. Le Correc Water Bay, Kowloon, Hong Kong, China a
Department of Civil and Environmental Engineering, The Hong Kong Univeristy of Science and Technology, Water Bay, Kowloon, Kong, ChinaAv. Rovisco Pais 1, 1049-001 Lisbon, Portugal IN+ Center for Innovation, Technology andClear Policy Research - Instituto Hong Superior Técnico, b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France a
a
Abstract Abstract Buildings use significant amount of energy worldwide, with mechanical air-conditioning systems accounting for a large proportion of the totaluse energy consumed. Utilizing natural ventilation achieve aair-conditioning comfortable indoor thermal environment whileproportion reducing Buildings significant amount of energy worldwide, withcan mechanical systems accounting for a large Abstract the use of air-conditioning and building energy consumption. However, previous studies mainly focused on either thermal comfort of the total energy consumed. Utilizing natural ventilation can achieve a comfortable indoor thermal environment while reducing or conservation by and utilizing natural ventilation. The correlation between studies thermalmainly comfort and energy performance due to theenergy use of air-conditioning building energy consumption. However, previous focused on either thermal comfort District networks are commonly addressed in the literature one of the effective solutions for decreasing the the effect heating of natural ventilation is important, but has not studied as thoroughly in most literature. ventilation in or energy conservation by utilizing natural ventilation. Thebeen correlation between thermal comfortMoreover, and energynatural performance due to greenhouse gas emissions from the building sector. Theseproperty, systems outdoor require high investments which are returned through thewere heat buildings is greatly affected by building geometry, material environmental condition and occupancy, which the effect of natural ventilation is important, but has not been studied thoroughly in literature. Moreover, natural ventilation in sales. to the changed climate studies. conditions building renovation policies, demandinformation in the future could (BIM) decrease, not fullyDue incorporated in theby previous Thisand paper presents a framework based heat on building modeling to buildings is greatly affected building geometry, material property, outdoor environmental condition and occupancy, which were prolonging the investment return period. study theincorporated effect of natural on the This correlation betweena thermal comfort energy performance. BIM provides not fully in theventilation previous studies. paper presents framework basedand on building information modeling (BIM)3D to The main scope of this papergeometric is to assess thematerial feasibility of using the heat as demand – outdoor temperature for heat demand building detailed information well the building and typefunction that help study themodels effect with of natural ventilation onand the correlation betweenasthermal comfort and location energy performance. BIMdetermine provides the 3D forecast. The district condition of Alvalade, in Lisbon (Portugal), was used as of a case study. The district is consisted 665 outdoor environmental and located occupancy, thereby improving the accuracy natural ventilation simulation. A case of study building models with detailed geometric and material information as well as the building location and type that help determine the buildings that using vary the in both construction period and attypology. Threetheweather (low,a medium, high) three district was conducted proposed framework, aimed investigating naturalscenarios ventilation residential flat inand Hong Kong at outdoor environmental condition and occupancy, thereby improving the accuracy of natural in ventilation simulation. A case study renovation scenarios were developed intermediate, deep). To estimate the error, obtained heat demand values were different seasons. Thethe results showframework, that(shallow, utilizing natural ventilation cannot always achieve thermal comfort. Natural ventilation was conducted using proposed aimed at investigating the natural ventilation in a residential flat in Hong Kong at compared with from a dynamic heatwhich demand previously developed and validated by the authors. brings cool air inresults late during themodel, indoor temperature canalways be controlled a comfortable and ventilation the energy different seasons. Thespring results(April) show that utilizing natural ventilation cannot achieve atthermal comfort.level Natural Thefor results showedventilation that when only weather change is considered, the margin of error could be acceptable for some applications use mechanical can be saved. The proposed framework helps evaluate the natural ventilation buildings for brings cool air in late spring (April) during which the indoor temperature can be controlled at a comfortable levelinand the energy (the error inindoor annual demand was lower than 20% foruse, all thereby weather creating scenarios considered). However, after introducing renovation maintaining thermal comfort at minimal energy a more sustainable built environment. use for mechanical ventilation can be saved. The proposed framework helps evaluate the natural ventilation in buildings for scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). maintaining indoor thermal atreserved. minimal energy use, thereby creating a more sustainable built environment. Copyright © 2018 Elsevier Ltd.comfort All rights ©The 2019 The Authors. Published byincreased Elsevier Ltd.average within the range of 3.8% up to 8% per decade, that corresponds to the value of slope coefficient on Selection peer-review under responsibility the22-139h scientific during committee ofheating the 10th season International Conference on Applied Energy of (ICAE2018). Copyright ©open Elsevier Ltd. rights reserved. This is anand article under the CCofof BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) decrease in2018 theaccess number of All heating hours the (depending on the combination weather and th The 10th International Conference on Applied Energy. Peer-review under responsibility of the scientific committee of ICAE2018 Selection and peer-review under responsibility of other the scientific committee of the 10– International Conference onper Applied Energy (ICAE2018). renovation scenarios considered). On the hand, function intercept increased for 7.8-12.7% decade (depending on the Keywords:Air ventilation assessment; building information modeling; energy efficiency; thermal comfort; integrated building design. coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and Keywords:Air ventilation assessment; building information modeling; energy efficiency; thermal comfort; integrated building design. improve the accuracy of heat demand estimations.
1. Introduction 1.©Introduction 2017 TheKong, Authors. Published by Elsevier Ltd. 61% of carbon emissions and 90% of energy consumption [1]. Given In Hong buildings account for nearly Peer-review under responsibility of the Scientific Committee of The 15th International Symposium onconsumption District Heating and theIn hotHong and humid Hong Kong, of mechanical ventilation approximately 40% Kong, summer buildingsweather accountoffor nearly 61%the of use carbon emissions and 90% of contributes energy [1]. Given Cooling. of in a of building [2]. Recent studies have shown that usingcontributes natural ventilation can achieve thethe hottotal andenergy humid consumption summer weather Hong Kong, the use of mechanical ventilation approximately 40% ofKeywords: the totalHeat energy consumption in a building [2]. Recent studies have shown that using natural ventilation can achieve demand; Forecast; Climate change
* Corresponding author. Tel.: (+852) 2358 8186; fax: (+852) 2358 1534. E-mail address:author. [email protected]. * Corresponding Tel.: (+852) 2358 8186; fax: (+852) 2358 1534. E-mail address: [email protected]. 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. th Selection peer-review under responsibility the scientific 1876-6102and Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10 International Conference on Applied Energy (ICAE2018). th Selection and peer-review under responsibility of the scientific committee of the 10 International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.971
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Vincent J.L. Gan et al. / Energy Procedia 158 (2019) 3319–3324 Author name / Energy Procedia 00 (2018) 000–000
a comfortable indoor thermal environment while reducing the energy consumption of mechanical ventilation. Thus, it is important to study the effect of natural ventilation on thermal comfort and energy performance. Computational fluid dynamics (CFD) is a common technique for studying the airflow in a ventilated environment. Gao and Lee [3] evaluated the natural ventilation performance and indoor temperature distribution in a typical residential unit in Hong Kong. Song and Meng [4] integrated CFD with a field study of the actual data of boundary conditions to improve the ventilation performance in a classroom. Several attempts have also been made to evaluate indoor air ventilation with different window opening configurations (i.e., single-sided and cross ventilation) [5]. As CFD simulation cannot directly predict thermal loading and energy consumption, building energy simulation (BES) programs have been applied to evaluate the energy performance of buildings [6]. Rijal et al. [7] used results from field surveys to help simulate the change of thermal environment and energy use due to different window opening behaviors. Burnett et al. [8] studied the wind effects on natural ventilation potential and energy savings in high-rise residential buildings. Similarly, Yik and Lun [9] studied the energy saving by utilizing natural ventilation in a highrise public housing in Hong Kong. Most of the previous studies focused on either thermal comfort or energy conservation by utilizing natural ventilation. In some cases, utilizing natural ventilation can reduce the energy consumption, but it may not be sufficient to maintain thermal comfort and therefore comprise the comfort index. The correlation between thermal comfort and energy performance due to the effect of natural ventilation is a challenging problem [10], but has not been studied thoroughly in literature. Besides, the simulation results for natural ventilation (e.g., temperature distribution) are greatly affected by the building geometry (such as dimension of structural component, size and position of window), material thermal property, outdoor environmental condition (such as wind and solar radiation) [11] and the room occupancy [12]. The previous studies did not comprehensively incorporate all these factors in the simulation, which may impose a large uncertainty on the results. Building information modeling (BIM) provides physical and functional characteristics of buildings [13], that can be used in CFD and BES for more accurate simulations on natural ventilation in buildings. Therefore, the objective of this study is to develop a BIM framework to analyze the effect of natural ventilation on the correlation between thermal comfort and energy performance in buildings. BIM provides detailed building geometry and material information that can be extracted to create the computational domains in CFD and BES. In addition, location-related information and building type (e.g., family, office, and hotel) in BIM can help determine the outdoor environmental conditions and the occupancy for more accurate simulations of natural ventilation. The proposed BIM framework serves as a decision support basis to improve the natural ventilation for maintaining thermal comfort to occupants at a minimal energy use, thereby creating a sustainable built environment. An illustrative example was prepared using the proposed framework, aimed at investigating the use of natural ventilation at different seasons for indoor thermal control and energy reduction. 2. Methodology The proposed BIM-supported framework is presented in this section. BIM is used as an information hub to interoperate CFD and BES for analyzing thermal comfort and energy performance concerning natural ventilation. As Figure 1 shows, the proposed framework includes four steps: (1) creation of BIM model, (2) CFD simulation, (3) BES modelling, and (4) result interpretation and analysis, which will be discussed in the following. (1) Creation of BIM model: The first step is to create a design BIM model. BIM provides detailed building geometry (and configuration) with accurate position of each individual building component (such as wall, column and slab) that are used to automatically generate the computational domains in CFD and BES. In addition, the material property information in design BIM models (such as thermal conductivity and solar transmittance) is taken to model the heat transfer process (e.g., heat conduction and solar radiation) in CFD and BES simulations. In addition to building geometry and material property, the location of the building can also be extracted from BIM to help determine the local weather profile and outdoor environmental conditions (such as wind, solar radiation, etc.). Finally, the building type for each individual room (such as residential or office) in BIM is used to help determine the occupancy pattern and evaluate the energy-related behavior in regard to building energy performance. With BIM, the proposed framework can provide a more efficient and accurate estimation on the indoor thermal environment and building energy performance.
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(2) CFD simulation: With the model geometry, material type, and computational domain exported from BIM, CFD simulation is carried out to evaluate the indoor temperature and flow field in order to evaluate the occupant thermal comfort at different periods. Eqs. (1) and (2) show the governing equations about the conservation of mass and momentum (also known as Navier-Stokes equation) for modeling the motion of the fluid: 𝜕𝜕𝜕𝜕 𝜕𝜕(𝜌𝜌𝑢𝑢𝑖𝑖 ) + =0 𝜕𝜕𝜕𝜕 𝜕𝜕𝑥𝑥𝑖𝑖
(1)
𝜕𝜕𝜕𝜕𝑢𝑢𝑖𝑖 𝜕𝜕(𝜌𝜌𝑢𝑢𝑖𝑖 𝑢𝑢𝑗𝑗 ) 𝜕𝜕𝜕𝜕 𝜕𝜕 𝜕𝜕𝑢𝑢𝑖𝑖 𝜕𝜕𝑢𝑢𝑗𝑗 + =− + [𝜇𝜇( + )] 𝜕𝜕𝜕𝜕 𝜕𝜕𝑥𝑥𝑗𝑗 𝜕𝜕𝑥𝑥𝑖𝑖 𝜕𝜕𝑥𝑥𝑗𝑗 𝜕𝜕𝑥𝑥𝑗𝑗 𝜕𝜕𝑥𝑥𝑖𝑖
(2)
The airflow rate, as determined from the CFD simulation, is used to measure the efficiency of natural ventilation expressed in terms of air change per hour (ACH). The ACH values are then used to predict the heat transfer via natural ventilation, as follows: 𝑄𝑄𝑁𝑁𝑤𝑤 = 𝐶𝐶𝑇𝑇 𝜌𝜌𝑎𝑎𝑎𝑎𝑎𝑎
𝐴𝐴𝐴𝐴𝐴𝐴 ∙ 𝑉𝑉 (𝑇𝑇𝑜𝑜𝑜𝑜𝑜𝑜 − 𝑇𝑇𝑖𝑖𝑖𝑖 ) 3600
(3)
where 𝑄𝑄𝑁𝑁𝑤𝑤 refers to the heat transfer by natural ventilation via an opening w, 𝐶𝐶𝑇𝑇 is the specific heat coefficient (J/kg·oC), 𝜌𝜌𝑎𝑎𝑎𝑎𝑎𝑎 represents the air density (kg/m3), (ACHˑV)/3600 stands for the steady state volumetric flow per second (m3/s), 𝑇𝑇𝑜𝑜𝑢𝑢𝑡𝑡 is the outdoor temperature (oC), and 𝑇𝑇𝑖𝑖𝑛𝑛 is the indoor thermostat temperature ( oC). The result of CFD simulation (𝑄𝑄𝑁𝑁𝑤𝑤 ) will be used in Step (3) for predicting the energy performance in buildings.
Figure 1. Flowchart of the proposed BIM-supported methodology framework
(3) BES modelling: The BES program models the heat transfer from natural ventilation and other heat sources (such as heat conduction, solar radiation, and metabolic heat gain of occupants) in predicting the thermal load and energy consumption, as follows: 𝑊𝑊
∑
𝑤𝑤=1
𝑄𝑄𝑁𝑁𝑤𝑤
𝐼𝐼
+ ∑ 𝑄𝑄𝑐𝑐𝑖𝑖 𝑖𝑖=1
𝐽𝐽
𝑗𝑗
𝐾𝐾
+ ∑ 𝑄𝑄𝑠𝑠 + ∑ 𝑄𝑄𝑜𝑜𝑘𝑘 = 𝑄𝑄𝑇𝑇 𝑖𝑖=1
𝑘𝑘=1
(4)
wherein 𝑄𝑄𝑁𝑁𝑤𝑤 refers to natural ventilation heat transfer via an opening w from Step (2), 𝑄𝑄𝑐𝑐𝑖𝑖 stands for heat transfer by conduction via a surface i, 𝑄𝑄𝑠𝑠𝑗𝑗 represents the solar radiation via a window j, 𝑄𝑄𝑜𝑜𝑘𝑘 is the metabolic heat gain from an occupant k, and QT is the total thermal load required to maintain the thermostat temperature. A BES program handles simulation for buildings exposed to time-varying climates, and predicts the energy consumption based on the thermal load (QT) from different heat sources. The energy efficiency of any particular building can then be analyzed. (4) Results interpretation and analysis: The results from CFD (including temperature distribution and flow field) and BES (ACH, thermal load, energy consumption, etc.) serve to determine the efficiency of natural ventilation. The proposed framework can be applied to study the changeover strategy between mechanical and natural ventilation at different times in order to achieve better occupant thermal comfort and energy savings in buildings.
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3. Illustrative Example A typical flat for the public housing in Hong Kong (see Figure 2 (a)) is created in BIM software for applying the proposed framework. The exterior walls of the flat are constructed from C40 concrete with mineral wool as the thermal insulation (conductivity = 0.053 W/m·oC). Based on the geo-location of the building in BIM, the weather profiles are extracted from a climate database. The building type in BIM, i.e., residential, helps determine the occupancy profile. The information is extracted for simulations in CFD and BES.
Figure 2. Overview of the configurations for (a) floor plan, (b) natural ventilation, and (c) mechanical ventilation
As Table 1 shows, April and July are selected during the cooling season (April – October) to analyze natural ventilation at different periods, because April has the least solar radiation and lowest temperature whereas July has the most solar heat gain from outdoor environment. CFD simulations are conducted for noon (12 AM) and night (7 PM) respectively, which affects the status of solar model in CFD. For natural ventilation scenarios, it is assumed that all the windows are kept open. The windows normal to the wind direction are defined as inlets with an inlet temperature obtained from the Hong Kong Observatory and an airflow rate determined from the external flow simulation (see Figure 2 (b)). For mechanical ventilation, the air-conditioner ducts are defined as the velocity inlets (with a supplied air temperature of 18˚C and an airflow rate of 0.12m3/s), while the air-conditioner vents are considered as the pressure outlets (see Figure 2 (c)). For mechanical ventilation scenarios, the BES program is further used to predict the amount of hourly energy consumption by air-conditioning. Table 1. Boundary conditions in CFD simulations for different scenarios Scenario
Ventilation type
Month
Time
Solar model Yes No Yes No Yes No Yes No
Inlet temperature (oC) 23a 19.5a 18 (AC) b 18 (AC) b 30a 26a 18 (AC) b 18 (AC) b
Boundary conditions Outdoor temperature (oC) 23a 19.5a 23a 19.5a 30a 26a 30a 26a
Airflow rate Shown on Figure 2d 0.12 m3/s b 0.12 m3/s b Shown on Figure 2d 0.12 m3/s b 0.12 m3/s b
Metabolic heat gain
1 Natural April Noon (12 AM) 2 Natural April Night (7 PM) 3 Mechanical April Noon (12 AM) 130 4 Mechanical April Night (7 PM) w/hour5 Natural July Noon (12 AM) personc 6 Natural July Night (7 PM) 7 Mechanical July Noon (12 AM) 8 Mechanical July Night (7 PM) a. Reference [14]; b. Reference [15]; c. Reference [16]; d. The airflow rates for natural ventilation were determined from external flow simulation in CFD. The flat is assumed at the top of the residential building (i.e., 40 floor) in CFD simulation, using reference wind speed of 2.7 m/s at 90 m height [14].
4. Results and Discussion Table 2 shows the indoor temperature from CFD, suggested temperature from WELL green building standard [17], thermal comfort level, and electricity consumption from BES. WELL is an international standard for measuring the health and wellbeing of occupants, and therefore was selected to evaluate the results. First, the energy simulation results are compared with the actual statistics for Hong Kong public housing [18]. The average hourly electricity consumption for air-conditioning calculated from the survey data is around 0.08 ± 0.03 kWh, which is close to the range of simulated electricity consumption of 0.04 to 0.11 kWh in this study. The proposed BIM framework improves the result accuracy, as the discrepancy between simulation and actual data is greatly reduced.
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Table 2. Indoor temperature and human thermal comfort level for different scenarios Indoor temperature for different ventilation types Scenario Month Ventilation Time Indoor Suggested Thermal Electricity type temperature temperature in comfort level consumption per 1 2 3 4 5 6 7 8
April April April April July July July July
Natural Natural Mechanical Mechanical Natural Natural Mechanical Mechanical
Noon Night Noon Night Noon Night Noon Night
(oC) 37 – 40 oC 20 – 21 oC 21 – 24 oC 20 – 21 oC 39 – 40 oC 26 – 27 oC 23 – 25 oC 21 – 22 oC
WELL (oC) 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC
Too hot Comfortable Comfortable Comfortable Too hot A bit warm Comfortable Comfortable
hour (kWh) 0 0 0.06 kWh 0.04 kWh 0 0 0.11 kWh 0.09 kWh
As Table 2 shows, enabling natural ventilation on April night can reduce the indoor temperature to around 2021oC, which meets the suggested range of 21-26oC in WELL. However, natural ventilation cannot always reduce the indoor temperature to meet the suggested temperature. For example, the indoor air temperatures with natural ventilation on April noon, July noon and July night are more than the maximum suggested value of 26oC, at which occupants feel uncomfortable and the mechanical ventilation should be used to control the indoor temperature.
Figure 3. Indoor temperature for natural and mechanical ventilation at (a) April noon, (b) April night, (c) July noon, and (d) July night
Figure 3 shows the indoor temperature distributions for natural and mechanical ventilation at different periods. As shown in Figure 3(a), the outdoor air temperature at noon of April is 23oC, so natural ventilation at this period carries cool air into the flat, which helps meet the suggested temperature for occupants (21-26oC) in WELL standard. However, if other important heat sources (such as metabolic heat gain and intense solar radiation) are also considered, the indoor air temperature increases considerably to above 37oC, substantially exceeding the maximum suggested temperature of 26oC. In such a case, occupants would feel uncomfortable and mechanical ventilation is required to achieve thermal comfort. Figure 3(a) shows that enabling mechanical ventilation reduces the indoor air temperature to around 21-24oC, which meets the WELL standard. But the use of mechanical ventilation also leads to an hourly electricity consumption of around 0.06 kWh. As shown in Figure 3(b), the indoor air temperature for natural ventilation at night of April ranges from 20-21oC, which is much lower than that at noon. This is because the outdoor temperature is relatively lower (19.5oC) and no solar radiation occurs at night. Due to these reasons, the indoor temperature at April night could be maintained at a desirable level by utilizing natural ventilation, and the mechanical ventilation system can be switched off, leading to an hourly saving in electricity consumption of 0.04 kWh. Figure 3(c) shows the simulation results at noon of July. Due to the higher outdoor temperature and more intense solar radiation, the average indoor air temperature at noon of July is 2-4oC higher than that in April. Natural ventilation cannot provide a comfortable thermal environment for occupants, therefore utilizing mechanical ventilation is
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necessary, resulting in an hourly energy consumption of 0.11 kWh which is 50% more than that in April due to the higher cooling load. The simulation results at July night, as shown in Figure 3(d), reflect the trade-off impact between occupant thermal comfort and building energy performance. Utilizing natural ventilation at night of July can reduce the indoor air temperature to around 26-27oC, which is slightly higher than the suggested temperature of 21-26oC in WELL. In this situation, occupants may feel a bit warm and prefer to use the mechanical ventilation for temperature control. However, if the occupants can accept the slightly higher indoor temperature (i.e., 27 oC), the use of mechanical ventilation can be avoided and the energy consumption can be reduced accordingly. This trade-off phenomenon (i.e., reducing energy consumption while compromising occupant comfort) mainly depends on the acceptable temperature of each individual in real life. The results can help occupants determine a changeover strategy between natural and mechanical ventilation to achieve more energy savings without significantly compromising occupant comfort.
4. Conclusions This paper presents a BIM framework to analyze the effect of natural ventilation on thermal comfort and energy performance in buildings. BIM provides information related to building geometry, materials, outdoor environment, and occupancy that can be integrated with CFD and BES for more accurate analyses on the natural ventilation. A case study was conducted, aimed at investigating the natural ventilation in a residential flat at different seasons. The results show that utilizing natural ventilation cannot always achieve thermal comfort. Natural ventilation airflow mostly carries cool air in late spring (such as April) during which the energy use for mechanical ventilation can be saved. The results from the framework help maintain a comfortable environment to occupants and enhance the energy efficiency in buildings. Other human comfort criteria (e.g., airflow) are also important and will be considered in the future. References [1] HKEPD. Greenhouse Gas Emission in Hong Kong by Sector. Hong Kong: Hong Kong Environmental Protection Department (HKEPD); 2012. [2] EMSD. Hong Kong Energy End-use Data. Hong Kong: Electrical & Mechanical Services Department (EMSD); 2014. [3] Gao CF, Lee WL. Evaluating the influence of openings configuration on natural ventilation performance of residential units in Hong Kong. Building and Environment. 2011;46:961-9. [4] Song J, Meng X. The improvement of ventilation design in school buildings using CFD simulation. Procedia Engineering. 2015;121:1475-81. [5] Shirzadi M, Mirzaei PA, Naghashzadegan M. Development of an adaptive discharge coefficient to improve the accuracy of cross-ventilation airflow calculation in building energy simulation tools. Building and Environment. 2018;127:277-90. [6] Harish V, Kumar A. A review on modeling and simulation of building energy systems. Renewable and Sustainable Energy Reviews. 2016;56:1272-92. [7] Rijal HB, Tuohy P, Humphreys MA, Nicol JF, Samuel A, Clarke J. Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings. Energy and Buildings. 2007;39:823-36. [8] Burnett J, Bojić M, Yik F. Wind-induced pressure at external surfaces of a high-rise residential building in Hong Kong. Building and Environment. 2005;40:765-77. [9] Yik FW, Lun YF. Energy saving by utilizing natural ventilation in public housing in Hong Kong. Indoor and built Environment. 2010;19:73-87. [10] Ali S, Kim D. Energy conservation and comfort management in building environment. Energy Conservation.2013;9:2229-44. [11] Malkawi A, Yan B, Chen Y, Tong Z. Predicting thermal and energy performance of mixed-mode ventilation using an integrated simulation approach. Building Simulation. 2016;9:335-46. [12] Bekö G, Toftum J, Clausen G. Modeling ventilation rates in bedrooms based on building characteristics and occupant behavior. Building and Environment. 2011;46:2230-7. [13] Eastman C, Eastman CM, Teicholz P, Sacks R, Liston K. BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors: John Wiley & Sons; 2011. [14] Hong Kong Observatory. Climatological Information Services. Hong Kong: Hong Kong Observatory; 2017. Available at: http://www.hko.gov.hk/contente.htm (accessed on 2 March 2018). [15] Hip Hing Engineering Development. RC-V815J Air Conditioner. Hong Kong: Hip Hing Engineering Development; 2018. Available at: http://hiphing8788.com/index.php?route=product/product&product_id=581 (accessed on 7 March 2018). [16] DCLG. UK's National Calculation Method for Non-Domestic Buildings. UK: Department for Communities and Local Government (DCLG); 2018. Available at: https://www.uk-ncm.org.uk/ (accessed on 7 March 2018). [17] IWBI. The WELL Building Standard. New York: International WELL Building Institute (IWBI); 2017. [18] Cheung C, Mui K, Wong L, Yang K. Electricity energy trends in Hong Kong residential housing environment. Indoor and built Environment. 2014;23:1021-8.
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Energy Procedia 158 Energy Procedia 00(2019) (2017)3319–3324 000–000 www.elsevier.com/locate/procedia
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China(ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China 15th International Symposium Districtof Heating and ventilation Cooling BIM-basedTheframework to analyze theoneffect natural on BIM-based framework to analyze the effect of natural ventilation on thermalthe comfort and energy performance in buildings Assessing feasibility of using the heat demand-outdoor thermal comfort and energy performance in buildings
a temperature forDeng a long-term heatC.P. demand Vincent function J.L. Gana, M. , Y. Tana, W.district Chena, Jack Chenga,*forecast a Vincent J.L. Gana, aM. Denga, Y. Tana, W. Chen , Jack C.P.c Chenga,* a,b,cof Civil and Environmental a b Univeristy of Science and Department Engineering, The Hong Kong I. Andrić *, A. Pina ,Clear P. Ferrão , J. Fournier ., B. Lacarrière , Technology, O. Le Correc Water Bay, Kowloon, Hong Kong, China a
Department of Civil and Environmental Engineering, The Hong Kong Univeristy of Science and Technology, Water Bay, Kowloon, Kong, ChinaAv. Rovisco Pais 1, 1049-001 Lisbon, Portugal IN+ Center for Innovation, Technology andClear Policy Research - Instituto Hong Superior Técnico, b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France a
a
Abstract Abstract Buildings use significant amount of energy worldwide, with mechanical air-conditioning systems accounting for a large proportion of the totaluse energy consumed. Utilizing natural ventilation achieve aair-conditioning comfortable indoor thermal environment whileproportion reducing Buildings significant amount of energy worldwide, withcan mechanical systems accounting for a large Abstract the use of air-conditioning and building energy consumption. However, previous studies mainly focused on either thermal comfort of the total energy consumed. Utilizing natural ventilation can achieve a comfortable indoor thermal environment while reducing or conservation by and utilizing natural ventilation. The correlation between studies thermalmainly comfort and energy performance due to theenergy use of air-conditioning building energy consumption. However, previous focused on either thermal comfort District networks are commonly addressed in the literature one of the effective solutions for decreasing the the effect heating of natural ventilation is important, but has not studied as thoroughly in most literature. ventilation in or energy conservation by utilizing natural ventilation. Thebeen correlation between thermal comfortMoreover, and energynatural performance due to greenhouse gas emissions from the building sector. Theseproperty, systems outdoor require high investments which are returned through thewere heat buildings is greatly affected by building geometry, material environmental condition and occupancy, which the effect of natural ventilation is important, but has not been studied thoroughly in literature. Moreover, natural ventilation in sales. to the changed climate studies. conditions building renovation policies, demandinformation in the future could (BIM) decrease, not fullyDue incorporated in theby previous Thisand paper presents a framework based heat on building modeling to buildings is greatly affected building geometry, material property, outdoor environmental condition and occupancy, which were prolonging the investment return period. study theincorporated effect of natural on the This correlation betweena thermal comfort energy performance. BIM provides not fully in theventilation previous studies. paper presents framework basedand on building information modeling (BIM)3D to The main scope of this papergeometric is to assess thematerial feasibility of using the heat as demand – outdoor temperature for heat demand building detailed information well the building and typefunction that help study themodels effect with of natural ventilation onand the correlation betweenasthermal comfort and location energy performance. BIMdetermine provides the 3D forecast. The district condition of Alvalade, in Lisbon (Portugal), was used as of a case study. The district is consisted 665 outdoor environmental and located occupancy, thereby improving the accuracy natural ventilation simulation. A case of study building models with detailed geometric and material information as well as the building location and type that help determine the buildings that using vary the in both construction period and attypology. Threetheweather (low,a medium, high) three district was conducted proposed framework, aimed investigating naturalscenarios ventilation residential flat inand Hong Kong at outdoor environmental condition and occupancy, thereby improving the accuracy of natural in ventilation simulation. A case study renovation scenarios were developed intermediate, deep). To estimate the error, obtained heat demand values were different seasons. Thethe results showframework, that(shallow, utilizing natural ventilation cannot always achieve thermal comfort. Natural ventilation was conducted using proposed aimed at investigating the natural ventilation in a residential flat in Hong Kong at compared with from a dynamic heatwhich demand previously developed and validated by the authors. brings cool air inresults late during themodel, indoor temperature canalways be controlled a comfortable and ventilation the energy different seasons. Thespring results(April) show that utilizing natural ventilation cannot achieve atthermal comfort.level Natural Thefor results showedventilation that when only weather change is considered, the margin of error could be acceptable for some applications use mechanical can be saved. The proposed framework helps evaluate the natural ventilation buildings for brings cool air in late spring (April) during which the indoor temperature can be controlled at a comfortable levelinand the energy (the error inindoor annual demand was lower than 20% foruse, all thereby weather creating scenarios considered). However, after introducing renovation maintaining thermal comfort at minimal energy a more sustainable built environment. use for mechanical ventilation can be saved. The proposed framework helps evaluate the natural ventilation in buildings for scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). maintaining indoor thermal atreserved. minimal energy use, thereby creating a more sustainable built environment. Copyright © 2018 Elsevier Ltd.comfort All rights ©The 2019 The Authors. Published byincreased Elsevier Ltd.average within the range of 3.8% up to 8% per decade, that corresponds to the value of slope coefficient on Selection peer-review under responsibility the22-139h scientific during committee ofheating the 10th season International Conference on Applied Energy of (ICAE2018). Copyright ©open Elsevier Ltd. rights reserved. This is anand article under the CCofof BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) decrease in2018 theaccess number of All heating hours the (depending on the combination weather and th The 10th International Conference on Applied Energy. Peer-review under responsibility of the scientific committee of ICAE2018 Selection and peer-review under responsibility of other the scientific committee of the 10– International Conference onper Applied Energy (ICAE2018). renovation scenarios considered). On the hand, function intercept increased for 7.8-12.7% decade (depending on the Keywords:Air ventilation assessment; building information modeling; energy efficiency; thermal comfort; integrated building design. coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and Keywords:Air ventilation assessment; building information modeling; energy efficiency; thermal comfort; integrated building design. improve the accuracy of heat demand estimations.
1. Introduction 1.©Introduction 2017 TheKong, Authors. Published by Elsevier Ltd. 61% of carbon emissions and 90% of energy consumption [1]. Given In Hong buildings account for nearly Peer-review under responsibility of the Scientific Committee of The 15th International Symposium onconsumption District Heating and theIn hotHong and humid Hong Kong, of mechanical ventilation approximately 40% Kong, summer buildingsweather accountoffor nearly 61%the of use carbon emissions and 90% of contributes energy [1]. Given Cooling. of in a of building [2]. Recent studies have shown that usingcontributes natural ventilation can achieve thethe hottotal andenergy humid consumption summer weather Hong Kong, the use of mechanical ventilation approximately 40% ofKeywords: the totalHeat energy consumption in a building [2]. Recent studies have shown that using natural ventilation can achieve demand; Forecast; Climate change
* Corresponding author. Tel.: (+852) 2358 8186; fax: (+852) 2358 1534. E-mail address:author. [email protected]. * Corresponding Tel.: (+852) 2358 8186; fax: (+852) 2358 1534. E-mail address: [email protected]. 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. th Selection peer-review under responsibility the scientific 1876-6102and Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10 International Conference on Applied Energy (ICAE2018). th Selection and peer-review under responsibility of the scientific committee of the 10 International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.971
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a comfortable indoor thermal environment while reducing the energy consumption of mechanical ventilation. Thus, it is important to study the effect of natural ventilation on thermal comfort and energy performance. Computational fluid dynamics (CFD) is a common technique for studying the airflow in a ventilated environment. Gao and Lee [3] evaluated the natural ventilation performance and indoor temperature distribution in a typical residential unit in Hong Kong. Song and Meng [4] integrated CFD with a field study of the actual data of boundary conditions to improve the ventilation performance in a classroom. Several attempts have also been made to evaluate indoor air ventilation with different window opening configurations (i.e., single-sided and cross ventilation) [5]. As CFD simulation cannot directly predict thermal loading and energy consumption, building energy simulation (BES) programs have been applied to evaluate the energy performance of buildings [6]. Rijal et al. [7] used results from field surveys to help simulate the change of thermal environment and energy use due to different window opening behaviors. Burnett et al. [8] studied the wind effects on natural ventilation potential and energy savings in high-rise residential buildings. Similarly, Yik and Lun [9] studied the energy saving by utilizing natural ventilation in a highrise public housing in Hong Kong. Most of the previous studies focused on either thermal comfort or energy conservation by utilizing natural ventilation. In some cases, utilizing natural ventilation can reduce the energy consumption, but it may not be sufficient to maintain thermal comfort and therefore comprise the comfort index. The correlation between thermal comfort and energy performance due to the effect of natural ventilation is a challenging problem [10], but has not been studied thoroughly in literature. Besides, the simulation results for natural ventilation (e.g., temperature distribution) are greatly affected by the building geometry (such as dimension of structural component, size and position of window), material thermal property, outdoor environmental condition (such as wind and solar radiation) [11] and the room occupancy [12]. The previous studies did not comprehensively incorporate all these factors in the simulation, which may impose a large uncertainty on the results. Building information modeling (BIM) provides physical and functional characteristics of buildings [13], that can be used in CFD and BES for more accurate simulations on natural ventilation in buildings. Therefore, the objective of this study is to develop a BIM framework to analyze the effect of natural ventilation on the correlation between thermal comfort and energy performance in buildings. BIM provides detailed building geometry and material information that can be extracted to create the computational domains in CFD and BES. In addition, location-related information and building type (e.g., family, office, and hotel) in BIM can help determine the outdoor environmental conditions and the occupancy for more accurate simulations of natural ventilation. The proposed BIM framework serves as a decision support basis to improve the natural ventilation for maintaining thermal comfort to occupants at a minimal energy use, thereby creating a sustainable built environment. An illustrative example was prepared using the proposed framework, aimed at investigating the use of natural ventilation at different seasons for indoor thermal control and energy reduction. 2. Methodology The proposed BIM-supported framework is presented in this section. BIM is used as an information hub to interoperate CFD and BES for analyzing thermal comfort and energy performance concerning natural ventilation. As Figure 1 shows, the proposed framework includes four steps: (1) creation of BIM model, (2) CFD simulation, (3) BES modelling, and (4) result interpretation and analysis, which will be discussed in the following. (1) Creation of BIM model: The first step is to create a design BIM model. BIM provides detailed building geometry (and configuration) with accurate position of each individual building component (such as wall, column and slab) that are used to automatically generate the computational domains in CFD and BES. In addition, the material property information in design BIM models (such as thermal conductivity and solar transmittance) is taken to model the heat transfer process (e.g., heat conduction and solar radiation) in CFD and BES simulations. In addition to building geometry and material property, the location of the building can also be extracted from BIM to help determine the local weather profile and outdoor environmental conditions (such as wind, solar radiation, etc.). Finally, the building type for each individual room (such as residential or office) in BIM is used to help determine the occupancy pattern and evaluate the energy-related behavior in regard to building energy performance. With BIM, the proposed framework can provide a more efficient and accurate estimation on the indoor thermal environment and building energy performance.
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(2) CFD simulation: With the model geometry, material type, and computational domain exported from BIM, CFD simulation is carried out to evaluate the indoor temperature and flow field in order to evaluate the occupant thermal comfort at different periods. Eqs. (1) and (2) show the governing equations about the conservation of mass and momentum (also known as Navier-Stokes equation) for modeling the motion of the fluid: 𝜕𝜕𝜕𝜕 𝜕𝜕(𝜌𝜌𝑢𝑢𝑖𝑖 ) + =0 𝜕𝜕𝜕𝜕 𝜕𝜕𝑥𝑥𝑖𝑖
(1)
𝜕𝜕𝜕𝜕𝑢𝑢𝑖𝑖 𝜕𝜕(𝜌𝜌𝑢𝑢𝑖𝑖 𝑢𝑢𝑗𝑗 ) 𝜕𝜕𝜕𝜕 𝜕𝜕 𝜕𝜕𝑢𝑢𝑖𝑖 𝜕𝜕𝑢𝑢𝑗𝑗 + =− + [𝜇𝜇( + )] 𝜕𝜕𝜕𝜕 𝜕𝜕𝑥𝑥𝑗𝑗 𝜕𝜕𝑥𝑥𝑖𝑖 𝜕𝜕𝑥𝑥𝑗𝑗 𝜕𝜕𝑥𝑥𝑗𝑗 𝜕𝜕𝑥𝑥𝑖𝑖
(2)
The airflow rate, as determined from the CFD simulation, is used to measure the efficiency of natural ventilation expressed in terms of air change per hour (ACH). The ACH values are then used to predict the heat transfer via natural ventilation, as follows: 𝑄𝑄𝑁𝑁𝑤𝑤 = 𝐶𝐶𝑇𝑇 𝜌𝜌𝑎𝑎𝑎𝑎𝑎𝑎
𝐴𝐴𝐴𝐴𝐴𝐴 ∙ 𝑉𝑉 (𝑇𝑇𝑜𝑜𝑜𝑜𝑜𝑜 − 𝑇𝑇𝑖𝑖𝑖𝑖 ) 3600
(3)
where 𝑄𝑄𝑁𝑁𝑤𝑤 refers to the heat transfer by natural ventilation via an opening w, 𝐶𝐶𝑇𝑇 is the specific heat coefficient (J/kg·oC), 𝜌𝜌𝑎𝑎𝑎𝑎𝑎𝑎 represents the air density (kg/m3), (ACHˑV)/3600 stands for the steady state volumetric flow per second (m3/s), 𝑇𝑇𝑜𝑜𝑢𝑢𝑡𝑡 is the outdoor temperature (oC), and 𝑇𝑇𝑖𝑖𝑛𝑛 is the indoor thermostat temperature ( oC). The result of CFD simulation (𝑄𝑄𝑁𝑁𝑤𝑤 ) will be used in Step (3) for predicting the energy performance in buildings.
Figure 1. Flowchart of the proposed BIM-supported methodology framework
(3) BES modelling: The BES program models the heat transfer from natural ventilation and other heat sources (such as heat conduction, solar radiation, and metabolic heat gain of occupants) in predicting the thermal load and energy consumption, as follows: 𝑊𝑊
∑
𝑤𝑤=1
𝑄𝑄𝑁𝑁𝑤𝑤
𝐼𝐼
+ ∑ 𝑄𝑄𝑐𝑐𝑖𝑖 𝑖𝑖=1
𝐽𝐽
𝑗𝑗
𝐾𝐾
+ ∑ 𝑄𝑄𝑠𝑠 + ∑ 𝑄𝑄𝑜𝑜𝑘𝑘 = 𝑄𝑄𝑇𝑇 𝑖𝑖=1
𝑘𝑘=1
(4)
wherein 𝑄𝑄𝑁𝑁𝑤𝑤 refers to natural ventilation heat transfer via an opening w from Step (2), 𝑄𝑄𝑐𝑐𝑖𝑖 stands for heat transfer by conduction via a surface i, 𝑄𝑄𝑠𝑠𝑗𝑗 represents the solar radiation via a window j, 𝑄𝑄𝑜𝑜𝑘𝑘 is the metabolic heat gain from an occupant k, and QT is the total thermal load required to maintain the thermostat temperature. A BES program handles simulation for buildings exposed to time-varying climates, and predicts the energy consumption based on the thermal load (QT) from different heat sources. The energy efficiency of any particular building can then be analyzed. (4) Results interpretation and analysis: The results from CFD (including temperature distribution and flow field) and BES (ACH, thermal load, energy consumption, etc.) serve to determine the efficiency of natural ventilation. The proposed framework can be applied to study the changeover strategy between mechanical and natural ventilation at different times in order to achieve better occupant thermal comfort and energy savings in buildings.
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3. Illustrative Example A typical flat for the public housing in Hong Kong (see Figure 2 (a)) is created in BIM software for applying the proposed framework. The exterior walls of the flat are constructed from C40 concrete with mineral wool as the thermal insulation (conductivity = 0.053 W/m·oC). Based on the geo-location of the building in BIM, the weather profiles are extracted from a climate database. The building type in BIM, i.e., residential, helps determine the occupancy profile. The information is extracted for simulations in CFD and BES.
Figure 2. Overview of the configurations for (a) floor plan, (b) natural ventilation, and (c) mechanical ventilation
As Table 1 shows, April and July are selected during the cooling season (April – October) to analyze natural ventilation at different periods, because April has the least solar radiation and lowest temperature whereas July has the most solar heat gain from outdoor environment. CFD simulations are conducted for noon (12 AM) and night (7 PM) respectively, which affects the status of solar model in CFD. For natural ventilation scenarios, it is assumed that all the windows are kept open. The windows normal to the wind direction are defined as inlets with an inlet temperature obtained from the Hong Kong Observatory and an airflow rate determined from the external flow simulation (see Figure 2 (b)). For mechanical ventilation, the air-conditioner ducts are defined as the velocity inlets (with a supplied air temperature of 18˚C and an airflow rate of 0.12m3/s), while the air-conditioner vents are considered as the pressure outlets (see Figure 2 (c)). For mechanical ventilation scenarios, the BES program is further used to predict the amount of hourly energy consumption by air-conditioning. Table 1. Boundary conditions in CFD simulations for different scenarios Scenario
Ventilation type
Month
Time
Solar model Yes No Yes No Yes No Yes No
Inlet temperature (oC) 23a 19.5a 18 (AC) b 18 (AC) b 30a 26a 18 (AC) b 18 (AC) b
Boundary conditions Outdoor temperature (oC) 23a 19.5a 23a 19.5a 30a 26a 30a 26a
Airflow rate Shown on Figure 2d 0.12 m3/s b 0.12 m3/s b Shown on Figure 2d 0.12 m3/s b 0.12 m3/s b
Metabolic heat gain
1 Natural April Noon (12 AM) 2 Natural April Night (7 PM) 3 Mechanical April Noon (12 AM) 130 4 Mechanical April Night (7 PM) w/hour5 Natural July Noon (12 AM) personc 6 Natural July Night (7 PM) 7 Mechanical July Noon (12 AM) 8 Mechanical July Night (7 PM) a. Reference [14]; b. Reference [15]; c. Reference [16]; d. The airflow rates for natural ventilation were determined from external flow simulation in CFD. The flat is assumed at the top of the residential building (i.e., 40 floor) in CFD simulation, using reference wind speed of 2.7 m/s at 90 m height [14].
4. Results and Discussion Table 2 shows the indoor temperature from CFD, suggested temperature from WELL green building standard [17], thermal comfort level, and electricity consumption from BES. WELL is an international standard for measuring the health and wellbeing of occupants, and therefore was selected to evaluate the results. First, the energy simulation results are compared with the actual statistics for Hong Kong public housing [18]. The average hourly electricity consumption for air-conditioning calculated from the survey data is around 0.08 ± 0.03 kWh, which is close to the range of simulated electricity consumption of 0.04 to 0.11 kWh in this study. The proposed BIM framework improves the result accuracy, as the discrepancy between simulation and actual data is greatly reduced.
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Table 2. Indoor temperature and human thermal comfort level for different scenarios Indoor temperature for different ventilation types Scenario Month Ventilation Time Indoor Suggested Thermal Electricity type temperature temperature in comfort level consumption per 1 2 3 4 5 6 7 8
April April April April July July July July
Natural Natural Mechanical Mechanical Natural Natural Mechanical Mechanical
Noon Night Noon Night Noon Night Noon Night
(oC) 37 – 40 oC 20 – 21 oC 21 – 24 oC 20 – 21 oC 39 – 40 oC 26 – 27 oC 23 – 25 oC 21 – 22 oC
WELL (oC) 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC 21 – 26 oC
Too hot Comfortable Comfortable Comfortable Too hot A bit warm Comfortable Comfortable
hour (kWh) 0 0 0.06 kWh 0.04 kWh 0 0 0.11 kWh 0.09 kWh
As Table 2 shows, enabling natural ventilation on April night can reduce the indoor temperature to around 2021oC, which meets the suggested range of 21-26oC in WELL. However, natural ventilation cannot always reduce the indoor temperature to meet the suggested temperature. For example, the indoor air temperatures with natural ventilation on April noon, July noon and July night are more than the maximum suggested value of 26oC, at which occupants feel uncomfortable and the mechanical ventilation should be used to control the indoor temperature.
Figure 3. Indoor temperature for natural and mechanical ventilation at (a) April noon, (b) April night, (c) July noon, and (d) July night
Figure 3 shows the indoor temperature distributions for natural and mechanical ventilation at different periods. As shown in Figure 3(a), the outdoor air temperature at noon of April is 23oC, so natural ventilation at this period carries cool air into the flat, which helps meet the suggested temperature for occupants (21-26oC) in WELL standard. However, if other important heat sources (such as metabolic heat gain and intense solar radiation) are also considered, the indoor air temperature increases considerably to above 37oC, substantially exceeding the maximum suggested temperature of 26oC. In such a case, occupants would feel uncomfortable and mechanical ventilation is required to achieve thermal comfort. Figure 3(a) shows that enabling mechanical ventilation reduces the indoor air temperature to around 21-24oC, which meets the WELL standard. But the use of mechanical ventilation also leads to an hourly electricity consumption of around 0.06 kWh. As shown in Figure 3(b), the indoor air temperature for natural ventilation at night of April ranges from 20-21oC, which is much lower than that at noon. This is because the outdoor temperature is relatively lower (19.5oC) and no solar radiation occurs at night. Due to these reasons, the indoor temperature at April night could be maintained at a desirable level by utilizing natural ventilation, and the mechanical ventilation system can be switched off, leading to an hourly saving in electricity consumption of 0.04 kWh. Figure 3(c) shows the simulation results at noon of July. Due to the higher outdoor temperature and more intense solar radiation, the average indoor air temperature at noon of July is 2-4oC higher than that in April. Natural ventilation cannot provide a comfortable thermal environment for occupants, therefore utilizing mechanical ventilation is
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necessary, resulting in an hourly energy consumption of 0.11 kWh which is 50% more than that in April due to the higher cooling load. The simulation results at July night, as shown in Figure 3(d), reflect the trade-off impact between occupant thermal comfort and building energy performance. Utilizing natural ventilation at night of July can reduce the indoor air temperature to around 26-27oC, which is slightly higher than the suggested temperature of 21-26oC in WELL. In this situation, occupants may feel a bit warm and prefer to use the mechanical ventilation for temperature control. However, if the occupants can accept the slightly higher indoor temperature (i.e., 27 oC), the use of mechanical ventilation can be avoided and the energy consumption can be reduced accordingly. This trade-off phenomenon (i.e., reducing energy consumption while compromising occupant comfort) mainly depends on the acceptable temperature of each individual in real life. The results can help occupants determine a changeover strategy between natural and mechanical ventilation to achieve more energy savings without significantly compromising occupant comfort.
4. Conclusions This paper presents a BIM framework to analyze the effect of natural ventilation on thermal comfort and energy performance in buildings. BIM provides information related to building geometry, materials, outdoor environment, and occupancy that can be integrated with CFD and BES for more accurate analyses on the natural ventilation. A case study was conducted, aimed at investigating the natural ventilation in a residential flat at different seasons. The results show that utilizing natural ventilation cannot always achieve thermal comfort. Natural ventilation airflow mostly carries cool air in late spring (such as April) during which the energy use for mechanical ventilation can be saved. The results from the framework help maintain a comfortable environment to occupants and enhance the energy efficiency in buildings. Other human comfort criteria (e.g., airflow) are also important and will be considered in the future. References [1] HKEPD. Greenhouse Gas Emission in Hong Kong by Sector. Hong Kong: Hong Kong Environmental Protection Department (HKEPD); 2012. [2] EMSD. Hong Kong Energy End-use Data. Hong Kong: Electrical & Mechanical Services Department (EMSD); 2014. [3] Gao CF, Lee WL. Evaluating the influence of openings configuration on natural ventilation performance of residential units in Hong Kong. Building and Environment. 2011;46:961-9. [4] Song J, Meng X. The improvement of ventilation design in school buildings using CFD simulation. Procedia Engineering. 2015;121:1475-81. [5] Shirzadi M, Mirzaei PA, Naghashzadegan M. Development of an adaptive discharge coefficient to improve the accuracy of cross-ventilation airflow calculation in building energy simulation tools. Building and Environment. 2018;127:277-90. [6] Harish V, Kumar A. A review on modeling and simulation of building energy systems. Renewable and Sustainable Energy Reviews. 2016;56:1272-92. [7] Rijal HB, Tuohy P, Humphreys MA, Nicol JF, Samuel A, Clarke J. Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings. Energy and Buildings. 2007;39:823-36. [8] Burnett J, Bojić M, Yik F. Wind-induced pressure at external surfaces of a high-rise residential building in Hong Kong. Building and Environment. 2005;40:765-77. [9] Yik FW, Lun YF. Energy saving by utilizing natural ventilation in public housing in Hong Kong. Indoor and built Environment. 2010;19:73-87. [10] Ali S, Kim D. Energy conservation and comfort management in building environment. Energy Conservation.2013;9:2229-44. [11] Malkawi A, Yan B, Chen Y, Tong Z. Predicting thermal and energy performance of mixed-mode ventilation using an integrated simulation approach. Building Simulation. 2016;9:335-46. [12] Bekö G, Toftum J, Clausen G. Modeling ventilation rates in bedrooms based on building characteristics and occupant behavior. Building and Environment. 2011;46:2230-7. [13] Eastman C, Eastman CM, Teicholz P, Sacks R, Liston K. BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors: John Wiley & Sons; 2011. [14] Hong Kong Observatory. Climatological Information Services. Hong Kong: Hong Kong Observatory; 2017. Available at: http://www.hko.gov.hk/contente.htm (accessed on 2 March 2018). [15] Hip Hing Engineering Development. RC-V815J Air Conditioner. Hong Kong: Hip Hing Engineering Development; 2018. Available at: http://hiphing8788.com/index.php?route=product/product&product_id=581 (accessed on 7 March 2018). [16] DCLG. UK's National Calculation Method for Non-Domestic Buildings. UK: Department for Communities and Local Government (DCLG); 2018. Available at: https://www.uk-ncm.org.uk/ (accessed on 7 March 2018). [17] IWBI. The WELL Building Standard. New York: International WELL Building Institute (IWBI); 2017. [18] Cheung C, Mui K, Wong L, Yang K. Electricity energy trends in Hong Kong residential housing environment. Indoor and built Environment. 2014;23:1021-8.