1. Introduction
Due to industrial development, the awareness of environmental problems is growing all over the world. Among them, the damage caused by global warming is rapidly increasing, and solutions are being sought around the world to solve it. As a result, paradigm shifts are taking place in the field of urban architecture. Green cities and architecture are in the spotlight all over the world to increase energy efficiency and ease environmental problems by utilizing renewable energy. Among the renewable energy used in green cities and architecture, wind energy is one of the essential factors because it has great economic potential and does not cause greenhouse effects.
Many studies have been conducted through wind tunnel experiments and computerized fluid dynamics on optimal location selection and on airflow characteristics around buildings to apply small wind power generation in urban areas. Richard F. Smith (2007) [
1] studied the analysis of airflows and the efficiency of installed wind turbines at the Bahrain World Trade Center via CFD (Computational Fluid Dynamics). Roy Denoon (2008) [
2] studied the efficient building form and layout during wind power generation through CFD and wind tunnel experiments. Lin Lu and Ka Yan Ip (2009) [
3] conducted a study of the wind speed between two buildings and the wind speed according to the height and roof shape of the building through CFD, indicating a three to eightfold increase in wind density depending on the height and roof shape of the building. Khayrullina, A. [
4] studied the efficiency of various wind turbines installed between buildings, and the location of wind turbines according to wind direction angles, turbulence, and the type of buildings. Ledo et al. [
5] conducted a study on the air flow characteristics of the wind power generator installed on the roof of a building, indicating that a flat roof has a larger wind energy density than other roofs and remains constant. Dursun Ayhan and Safak Salglam [
6] analyzed the efficiency of wind turbines installed in downtown buildings according to the geometry of buildings through CFD. The analysis showed that wind turbines increased up to eight times as high as buildings. Abohela et al. [
7] conducted a study to select the optimal location for installing small wind power generators on roofs according to different roof shapes and wind angles, showing that the maximum acceleration of wind speed occurred on arched roofs, which can increase energy acquisition by up to 56.1%. In order to utilize wind energy in urban areas, Campbell et al. [
8] proposed three methods for applying wind power systems:
- (1)
Independent installation of wind power generators through site selection in urban areas;
- (2)
Installation of wind power generators in existing buildings;
- (3)
Integrate wind generators into buildings (Building Integrated Wind Power).
Buildings are more concentrated in downtown areas, so there is a great difficulty in selecting sites to install wind power generators independently. Building Integrated Wind Power (BIWP), which incorporates wind turbines into buildings, is economical and efficient without the need for support to position turbines to installation height. However, the large scale of wind power generation can cause noise and vibration. In recent years, micro wind power generation systems (Micro Wind Turbine) have mainly been applied. Small wind power generators are defined as having a performance of 2.5 kW or less [
9], or a rotor diameter of 1.25 m or less [
10].
Generally, the Reynold-Average Navier–Stokes (RANS) simulation is the most widely used method for modeling the flow turbulence due to the well-developed CFD best practice guidelines, but it has some inherent limitations for modeling complex flow and unsteady flow structures [
11,
12,
13,
14]. The direct numerical simulation (DNS) would be prohibitive for flow with high Reynolds numbers in present study. Thus, we choose the LES (Large Eddy Simuation) approach to solve the problem with affordable computational costs, which is also considered as the approach with the most potential by many researchers [
11,
14]. Generally, the LES research on the flow field around low-rise buildings mainly focuses on the case of an isolated building without snowdrift [
15,
16,
17,
18,
19]. Some scholars have considered the influence of the surrounding buildings on the flow characteristics [
20,
21,
22]. These numerical studies have been well verified by wind tunnel experiments or field measurements.
According to Ledo et al. [
23], the installation of small wind power generators in urban buildings is subject to restrictions due to low wind speeds, high turbulence intensity, and recognition of noise generated by turbines. In addition, air flow characteristics around buildings vary depending on the shape or size of buildings, layout, spacing, wind direction, and surface classification [
24,
25,
26]. Therefore, research on optimal installation locations with high wind speeds and low turbulence intensity is needed to increase the efficiency of wind turbines. There are various ways in which small wind farms are installed in buildings. In this paper, wind tunnel experiments and CFD analyses were conducted to analyze the effects of wind speed and turbulence on small wind power generators installed on rooftops due to changes in the height and porosity of mid- to low-rise buildings in the city.
As such, many studies have been conducted to apply wind power generators in downtown buildings and to check the efficiency of wind power generation for various roof types of buildings. However, a safety railing is installed on the rooftop of the actual building. If a railing is installed on the rooftop floor of a building in the city center, it will have different air flow characteristics from the top of the rooftop; thus, the analysis of air flow in the rooftop floor of a building with railings is insufficient. Therefore, in this paper, we want to analyze the wind tunnel experiment and computational fluid dynamics of the upper air flow characteristics according to the porosity and height of the parapet installed in the building for optimal efficiency when installing the actual wind power generator.
4. Results and Discussions
A computational fluid analysis was conducted to determine the optimal location of wind power generators by analyzing the air flow characteristics of the upper air flow rate and height of the parapet installed on the upper roof of the actual building. Although wind speed contributes greatly to the performance of wind power generators, the impact on the fatigue life of wind power generators should be minimized by providing homogeneous wind quality by identifying locations where turbulence is less affected. To minimize the effects of turbulence, Islam Abohela [
7] conducted a study on the location of rooftop wind turbines according to the roof types of various buildings. When wind turbines are installed, turbulence intensity is greater than 1.3 H. In addition, according to the Encraft Warwick Wind Trials Project [
13], the lowest position of a wind generator rotor is proposed to be at least 30% of the minimum building height at the top of the roof, and the WINEUR [
14] report suggests 35% to 50% of the building height. Therefore, in this study, less than 1.3 H, which produces significant turbulence intensity, was named Turbulence Area, and wind speed ratio in the turbulent area was not considered.
4.1. Selection of Wind Angle
In order to find the most advantageous wind angle when installing wind power generators, the analysis was conducted on wind direction angles of 0 and 45 degrees. Since the performance of the wind generator is greatly contributed to by the average wind speed, the surface roughness was interpreted for the surface roughness D, where the average wind speed is dominant. The conditions used in the analysis are shown in
Table 3.
Table 6 shows the maximum wind speed ratio and turbulence intensity ratio and location of the roof layer of the building according to the wind direction. At 0 degrees wind direction angle, the maximum wind velocity ratio is 1.3
at the top of the turbulence zone. At 45 degrees wind direction angle, the maximum wind velocity ratio is at (55) of 1.3
at the top of the turbulence zone. In addition, the maximum wind speed ratio is 0.37% smaller than the wind direction angle of 0 degrees. The maximum wind speed ratio according to changing angle of wind direction was not significantly changed within 1%. However, in the case of turbulent intensity ratio, wind direction angle of 45 degrees was 31% smaller than that of 0 degrees. Therefore, the difference in the maximum wind speed ratio is not significant, and the wind angle of 45 degrees, where the maximum wind speed ratio occurs, is more advantageous when installing wind power generators than a wind speed of 0 degrees.
Figure 10 shows the maximum wind velocity ratio and turbulence intensity ratio at the top of the rooftop according to the change in height of the wind direction angle.
4.2. Parapet Impact Analysis
In order to apply small wind power generation from the rooftop of the building, the air flow analysis was conducted on the upper part of the rooftop. In fact, railings are installed on the rooftop floor of a flat roof building in accordance with the Enforcement Decree of the Building Act for safety. The installation of these handrails has a significant effect on airflow at the top of the rooftop. A computational fluid analysis was performed to analyze the air flow characteristics of the upper roof layer according to the porous rate of the handrail and the height of the handrail.
The impact analysis of the parapet installed on the upper part of the rooftop was conducted on the same location and height where the maximum wind speed occurs on the flat roof without the railing installed.
Table 7 shows the location and height of the maximum wind speed ratio of Case N and the maximum wind speed ratio and turbulence intensity ratio.
Table 8 shows the wind speed ratio and turbulence intensity ratio of the case with the parapet installed at the same height and location of Case N. The height of the analysis of the case with a parapet height of 0.3
at the surface roughness D was 1.4 H because the railing is located at the height of Case N.
4.2.1. Parapet Height
Figure 11 and
Figure 12 show the wind speed ratio and turbulence intensity ratio of porous stars according to the height of the parapet by surface roughness. Regardless of the height and porosity of the parapet, wind speed ratio is lower than that of no railing. As the height of the parapet increases, the wind speed ratio decreases, and the turbulence intensity ratio tends to increase in cases with low porosity. However, if the porosity rate is 80%, the wind speed reduction effect by the parapet is reduced, and the turbulence intensity ratio decreases as the height of the parapet increases, and is lower than Case N. The effect of reducing turbulence intensity by parapet is significant from 0.2 H to 0.3 H, resulting in a 33% and 43% decrease in surface roughness D, respectively, and an 11% and 27% decrease in surface roughness B, respectively. Therefore, as the height of the parapet with sufficient porosity increases, the effect of reducing turbulence intensity is also increased.
4.2.2. Parapet Porosity
Figure 13 and
Figure 14 show the wind speed and turbulence intensity ratios by parapet height according to changes in porosity by surface roughness. As the porous rate of handrails increases, wind speed ratio increases, and turbulence intensity ratio decreases. If the porosity rate is low at 0% and 30%, the turbulence intensity ratio is higher than Case N, regardless of the height of the handrail, and about three times higher in Case 30–0.2. However, if the porosity rate is high at 80%, the turbulence intensity ratio is lower than that of no railing, and it decreases by up to 43%. Therefore, the increase in the parapet porosity results in a significant reduction in turbulence intensity.
4.2.3. Airflow Distribution inside Parapet
The air flow distribution was shown to determine the effect of air flow inside the roof top layer parapet. The target case has a height of 0.3 H and was shown for 30%, 50%, and 80% to see the effect of the porosity. The air distribution was represented by horizontal and vertical distribution, and the horizontal distribution was represented at 0.15 H, one-half the height of the parapet, while the vertical distribution was represented in the middle of the building, parallel to the wind direction.
Figure 15 shows the vertical distribution representation area.
Figure 16 and
Figure 17 show the airflow flow diagram inside the parapet of surface roughness D and B. As the porosity increases, both D and B exhibit similar airflow patterns. Case 30–0.3 shows that vortex occurs widely in the middle of the rooftop. The increase in porosity shows that in Case 50–0.3 the wind velocity of airflow through the parapet increases, dividing the vortex around the middle, and in Case 80–0.3 the range of the vortex becomes narrow and dissipates.