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Journal of the Korea Institute of Ecological Architecture and Environment - Vol. 17, No. 1, pp. 23-28
Abbreviation: J. Korea Inst. Ecol. Archit. And Environ.
ISSN: 2288-968X (Print) 2288-9698 (Online)
Print publication date 28 Feb 2017
Received 09 Jan 2017 Revised 25 Jan 2017 Accepted 30 Jan 2017
DOI: https://doi.org/10.12813/kieae.2017.17.1.023

The verification about possibility of introducing Window to Floor Ratio as design index for building energy performance
Choi, Won-Ki* ; Lee, Yong-Jun* ; Lee, Hyun-Soo** ; Eom, Jae-Yong*** ; Lee, Chung-Kook****
*SONUSYS, South Korea
**Eco-Facade Eng. Lab, BEL Technology, South Korea
***Department of Architectural Eng., Graduate School, Inha University, South Korea
****Corresponding author, Climate Change Research Institute of Korea, South Korea (chungkugi@naver.com)


ⓒCopyright Korea Institute of Ecological Architecture and Environment
Funding Information ▼

Abstract
Purpose

Many design index that are using in planning phase have been developed. The most popular things among them are Window to Wall Ratio and Surface to Volume Ratio. However there are some limits. Window to Wall Ratio cannot consider building size and Surface to Volume Ratio cannot do Window to Wall Ratio. Accordingly, in this paper, the Window to Floor Ratio was proposed that it can be considered both building size and Window to Wall Ratio. And analyzed correlation of energy demand.

Method

For the test, 16 modules with the size of 6m x 6m x 4m were used to make 35 models with the same volume. The simulation was conducted to 945 cases using the window-to-wall ratio of 30, 50 and 70 % in three areas such as Seoul, Gwangju and Jeju and three kinds of windows. And IES_VE was used.

Result

The findings above show that the Window to Floor Ratio that can be considered both building size and Window area have to become as design index. It was found out that design criteria with SHGC is necessary, not with the thermal performance (U-value). It is needed to additional analysis about residential building and the effect of 24-hours heating and cooling condition. It plans to carry out research to establish design indicators for climatic conditions in the country and building applications.


Keywords: Building energy, Solar heat coefficient, Window to floor ratio, Office building, Design index
키워드: 건물에너지, 태양열취득계수, 창바닥비, 업무용건물, 설계지표

1. Introduction
1.1. Background and Purpose of Study

The energy consumption of building is influenced by various element technologies. These technologies can be represented by passive or active technologies. However, while these technologies are often considered in the building design stage, they are generally selected based on the aimed energy performance and cost. However, the building shape, window area and direction which are basically considered in the building design stage are the most common planning factors .

Design indicators are the relationship between these design factors and building energy performance. Various design indicators are being developed and utilized all over the world. However, most of these indicators are focused on residential buildings where the heating energy becomes main, and it is analyzed that there is a limit to apply to office buildings like this paper. Therefore, this study was performed to comprehensively analyze the impact on building energy of area, window to wall ratio, window performance, and shape on building energy in buildings with the same volume, and to provide reasonable design indicators by deriving the correlation with various design indicators.

1.2. Method and Scope of Study

This study, as simulation study using IES_VE, was performed using weather data of Seoul, Gwangju and Jeju area. This is because energy saving design standards are set up in South Korea, which is divided into the central region of Seoul, the southern region of Gwangju, and the Jeju region. And window area was targeted to 30, 50, 70%. The window performance was also analyzed in three types considering heat transmission coefficient and SHGC.

The analytical model was defined by using column spacing and floor height of 6 m * 6 m * 4 m office building, unit module, and performed energy performance and sensitivity analysis for 35 models that can be composed through 16 modules combination of previous studies. As design indicators, the correlation was derived using the window to wall ratio, surface to volume ratio, window to floor ratio, etc.


2. Analysis Model and Input Conditions

This study is the comprehensive analysis of the effects of window performance changes on the basis of various building shapes with the same volume according to the combination of unit module. For this, a model with 6 m × 6 m and 4.2 m height with ratio of lateral to longitudinal length 1: 1 is presented, and 16 cases of module combinations presented in the previous study (Choi Won-gi et al., 2007) were further subdivided, and simulation analysis was performed on this. Table 1 through Table 3 summarize the arrangement patterns of 1, 2, 4, 8, and 16-floor models according to module combination. The wall composition and property values for the unit module are set as shown in Table 4 based on the building energy saving design standards applied since January 2013 announced by the Ministry of Land, Infrastructure, and Transport. Table 5 summarizes the performance data of the applied windows. As can be seen in Table 6, the selection standard for the window performance consists of single Low-e double glazing, which is the most widely used, triple Low-e double glazing, which has low solar heat gain coefficient (SHGC), and a single Low-e triple glazing, which has similar insulation performance is to this but high solar heat gain coefficient (SHGC). The reason for choosing this window performance is to compare the maximum insulation performance and the general insulation performance that can be composed by double glazing, and next, to compare the effect when the insulation performance (heat conduction ratio) is similar, but SHGC is different.

Table 1. 
1st Floor Analysis Cases According to Module Combination
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Model
Position
Model 7 Model 8 Model 9 Model 10 Model 11 Model 12
Model
Position
Model
Position
Model 13 Model 14 Model 15

Table 2. 
2nd Floor Analysis Cases According to Module Combination
Model 16 Model 17 Model 18 Model 19 Model 20
Model
Position
Model 21 Model 22 Model 23 Model 24 Model 25
Model
Position

Table 3. 
Over 4th Floor Analysis Cases According to Module Combination
Model 26 Model 27 Model 28 Model 29 Model 30
Model
Position
Number
of
stories
4 4 4 4 4
Model 31 Model 32 Model 33 Model 34 Model 35
Model
Position
Number
of
stories
4 8 8 8 16

Table 4. 
Material Properties & Wall Composition
Material Conductivity
(W/m․℃)
Density
(kg/㎥)
Specific Heat
(J/kg․℃)
1) Stone(Granite) 3.30 2,700 900
2) Insulator(Extrusion Special Grade) 0.027 600 1,400
3) Concrete(1:2:4) 1.60 2,200 1,000
4) Cement Mortar(1:3) 1.4 2,000
5) Gypsum Board 0.18 800 837
Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 U-value
(W/㎡․℃)
Exterior Wall 1) 30㎜ 2) 90㎜ 3) 150㎜ 4) 20㎜ 5) 25㎜ 0.267
Roof 3) 100㎜ 2) 140㎜ 4) 30㎜ 2) 150㎜ 0.182
Floor 3) 70㎜ 4) 30㎜ 3) 100㎜ 2) 85㎜ 0.285
Slab 3) 150㎜ 5) 25㎜ 2.209
Inside Wall 5) 25㎜ 3) 100㎜ 5) 25㎜ 1.785

Table 5. 
Glazing Configuration & Properties
Single Low-e
Double Glazing
Triple Low-e
Double Glazing
Single Low-e
Triple Glazing
Spec.
24mm(6+12+6) 28mm(6+16+6) 42mm(6+12+6+12+6)
U-Value SHGC VLT U-Value SHGC VLT U-Value SHGC VLT
1.7519 0.6155 0.734 1.0997 0.1678 0.277 1.0178 0.4929 0.615
U-value
of Window
1.9039 W/㎡K 1.3170 W/㎡K 1.2433 W/㎡K

In order to analyze the heating and cooling energy demand of the building, it is necessary to present various setting values such as occupancy density, illumination heat generation, device heat generation, occupancy schedule, and heating and cooling schedule, and the factors and setting conditions of the building subject to simulation in this study are assumed as shown in Table 6.

Table 6. 
Simulation Input Data
Contens Input Data
Room Temperature Heating : 20℃
Cooling : 26℃
Building Operation
Schedule
Weekdays : 08:00∼18:00
Weekend : Off
Person 0.11 people/㎡
Human 126 W/person
Facilities 15 W/㎡
Target Illumination 400 lux
Lighting 3.4 W/㎡・100 lux
(Non-Dimming Control)
Infiltration & Ventilation 0.3 times/h, 60㎥/man․h
[Large Office]
HVAC Ideal Load Air System
Wether Data Seoul, Gwangju, Jeju
IES_VE Data

Finally, the meteorological data used were analyzed by applying Seoul, Gwangju and Jeju area weather data provided by IES_VE. Figure 1 shows the distribution of monthly average outside temperature, and Figure 2 shows the Global Horizontal Irradiance distribution.


Fig. 1. 
Regional Monthly Average Outdoor Temperature


Fig. 2. 
Regional Monthly Average Total Solar Radiation

Examining Global Horizontal Irradiance, it can be seen that Seoul, Gwangju and Jeju are quite different. In particular, in case of Jeju, the distribution of Global Horizontal Irradiance is very high from March to September. In case of Seoul and Gwangju, it can be seen that the values of Global Horizontal Irradiance are relatively high in April, May and June.

These regional differences, that is, the energy performance of the same-volume buildings according to the central, southern, and Jeju regions, are also compared and analyzed to provide reasonable standards for each region, and further suggested the reasonable window standards and window to wall ratio standards.


3. Analysis of Simulation Results
3.1. Analysis of Energy Demand

Figure 3 shows the annual heating and cooling energy demand of single Low-e Double Glazing by model. Although there is a difference in each model, the distribution pattern of energy demand is very similar. In particular, it can be seen that the 70% model of the window to wall ratio in Jeju shows a difference of more than 30 MWh compared to the 30% model of the window to wall ratio.


Fig. 3. 
Anual Energy Demand of Single Low-e Double Glazing

Figure 4 shows the annual heating and cooling energy demand of the triple Low-e Double Glazing by model. Although there is a difference in the value of each model, it can be seen that the energy demand distribution is very low compared with the window made of single Low-e. And Jeju area is characterized by superior performance at the same window to wall ratio compared to other areas. Figure 5 shows the annual heating and cooling energy demand of single Low-e Triple Glazing by model.


Fig. 4. 
Anual Energy Demand of Triple Low-e Double Glazing


Fig. 5. 
Anual Energy Demand of Single Low-e Triple Glazing

Although there is a difference in the energy demand reviewed by model, it is very similar to that of the single Low-e double glazing, and in the model with excellent energy performance, the difference according to the window to wall ratio is not large, but in the model with relatively low the energy performance, the difference is about 40 MWh or more.

Figure 6 shows the distribution and correlation of regional energy demand according to the floor area ratio regardless of the window to wall ratio (WFR) in case of single Low-e double glazing. On the whole, the larger the window to wall ratio (WFR) is, the greater the energy demand is, which is the result of the analysis consistent with previous studies. However, there are some differences in the correlation equation, which is analyzed as a result of the difference in window performance.


Fig. 6. 
Regional Energy Demand of Single Low-e Double Glazing according to WFR

Figure 7 shows the regional energy demand distribution and correlation according to the floor area ratio regardless of the window to wall ratio (WFR) in case of the Triple Low-e Double Glazing. On the whole, the larger the window to wall ratio (WFR) is, the greater the energy demand is, but as the analysis shows, Jeju region has the best performance as heat transmission coefficient is good and the window with low SHGC is applied.


Fig. 7. 
Regional Energy Demand of Triple Low-e Double Glazing according to WFR

Figure 8 shows the regional energy demand distribution and correlation according to the floor area ratio regardless of the window to wall ratio (WFR) in case of the Single Low-e Triple Glazing. On the whole, the larger the window to wall ratio (WFR) is, the greater the energy demand is, and shows similar pattern to the single Low-e Double Glazing.


Fig. 8. 
Regional Energy Demand of Single Low-e Triple Glazing according to WFR

However, it shows a pattern contrary to the triple low-e double glazing, and it can be confirmed that the energy saving effect can not be expected when the heat transmission coefficient is simply increased. Figure 9 shows the energy demand distribution according to the S/V ratio. It is considered that there is a limit to find any correlation and the analysis is omitted.


Fig. 9. 
Regional Energy Demand of Single Low-e Double Glazing according to S/V rate

And figure 10 shows the energy demand distribution according to the S/V ratio. It is considered that there is a limit to find any correlation and the analysis is omitted.


Fig. 10. 
Regional Energy Demand of Single Low-e Double Glazing according to S/R rate


4. Conclusion

This paper conducted the analysis through simulation with a focus on the development of indicators available at the design stage concerning the global trends in the reduction of greenhouse gas emissions according to global warming. The results are summarized as follows.

First, the window to wall ratio, area volume ratio and area bottom ratio widely used as indicators are proved to be limitations in the design indicators

Second, as the window to wall ratio increases, the energy demand also increases, but there is a limit to derive the correlation as the region and window performance varies.

Third, by region, across all models, the correlation between mutual window to floor ratio (WFR) was proved to be proportional, and the window volume ratio (WVR) also proved to have the same correlation.

Fourth, it is reasonable to adopt Window to Floor Ratio as the design indicator for office buildings, which is because the building size and window area are considered simultaneously, and the window volume ratio can be adopted by the same principle.

Fifth, in order to reduce building energy consumption through the existing buildings energy-saving design standard, the standard for SHGC should be included and the standard based on Window to Floor Ratio (WFR) should be prepared.

Through the above study, it can be proved that the window to floor ratio (WFR) which can simultaneously consider the window area and the building size as the design indicator was the most desirable, and it is urgent to establish design standards through the solar heat gain coefficient (SHGC), not insulation performance.


Acknowledgments

This research was supported by a grant(16AUDP-B0791 04-03) from Architecture & Urban Development Research Program(AUDP) funded by Ministry of Land, Infrastructure and Transport of Korean government.


References
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