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Numerical Analysis of Building Aerodynamic forWind Energy Harvesting

Liana Zahal, S3265485

22/10/2013

1 INTRODUCTION

Wind energy is regarded as a clean and efficient energy generation method. Wind is deemedas a clean source of energy as it provides relevant benefits in terms of both pollutionreduction and fuel savings. Increasing demand for renewable energy source has increase theinstallation for wind turbines in various locations including open areas and offshore. Recently,implementation of wind turbines in urban and sub urban location has increase. Wind turbineinstallations near urban areas allow an efficient generation method to supply energy to thesurrounding buildings. As the energy is generated in-situ, energy dispatch system is muchsimpler and energy losses can be minimized (Balduzzi, 2012). The buildings in urban and suburban area can also create an accelerating effect on the wind, which can possibly increase theamount of energy density generated by the wind turbines. Another interesting idea is to installwind turbines at the top of a tall building, at a height that could not be reached by installationtowers. This gives possibility to exploit a faster flow without the need of high towers, thusreducing the capital cost of machine as well as installation cost. The benefits of urban windturbines installation aforementioned leads to an increment in researches performed under thisfield. However, it should be noted that the real feasibility of this scenario has yet to be proved,both in terms of real energy harvesting and of the compatibility of the turbines with a denselypopulated area. This study will critically investigate the accelerating effects of surroundingbuildings configuration on the wind velocity.

Part of this study is to model an arbitrary building configuration which closely represents atypical sub urban site. A typical mean height was chosen for the buildings, and the windturbine installation building is made to be significantly higher than buildings mean height. Abuilding, indicated as upwind building which is slightly higher than the mean height is placedat the front of the installation building. The main goal of this study is to investigate the effectof different distances between upwind building and the installation building on the flowaccelerating effect.

In this study, a standard k-epsilon turbulence model is selected to model the atmospheric flow.Based on study done on several journals, standard k epsilon turbulence model can provide areasonably good fit with experimental result for atmospheric flow cases. This model canprovide an accurate as well as efficient usage of computational resources. CFD techniquesmay produce error in results, thus it is important to validate against an establishedmeasurement. In this study, a validation is done against a result from a published journal. Acomparison between 2D and 3D cases will also be provided.

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Modelling an atmospheric wind flow requires an extensive research on the appropriateboundary conditions for the inlet. This is important to ensure the modelled flow is realisticand comparable to the natural wind flow. The boundary conditions include velocity profile,turbulent kinetic energy and turbulent dissipation rate. Mesh refinement is performed on thebasis of a sensitivity analysis on the cells’ number, to ensure grid-independency of the results.

This report consists of three main sections which are the model description, results anddiscussion and conclusion. Model descriptions include the model geometry, computationalflow domain and the boundary conditions. The results analysis is included in the results anddiscussion section. Conclusive remark will be made at the end of this report.

2 MODEL DESCRIPTIONS

2.1 Model Geometry

Figure 1: Building Model Geometry

Figure 1 shows the overall buildings configuration inside the flow domain. The buildingconfiguration is made out of three main elements which are the installation building (IB)where the wind turbine will be installed, upwind building (UB) which act as a flowaccelerator and roughness elements (Zo) which are considered as surrounding buildings with

mean height (Ĥ). In this study, the distance (D) between UB and IB will be varied to check

for the effects of wind acceleration.

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Mean Height, Ĥ 5m

Buildings Height Width Length

Installation Building [IB] 30m 6Ĥ 15m 3Ĥ 15m 3Ĥ

Upwind Building [UB] 10m 2Ĥ 15m 3Ĥ 15m 3Ĥ

Roughness Elements [Zo] 5m 1Ĥ 15m 3Ĥ 15m 3Ĥ

Table 1: Buildings Dimension

Table 1 shows the buildings dimension in terms of metre as well as non-dimensionalized

parameter, which is the mean height, Ĥ. It should be noted that the mean height value is taken

as 5m, as it can be assumed as an average height of buildings in a sub urban area. Thedistance between roughness elements and UB is kept constant throughout the entiresimulations. The roughness elements are modelled explicitly, to recreate a wind profile at theend of the last element with the same displacement of the wind profile imposed at the inletboundary. The variable in this study is the distance, D between the UB and IB as tabulated inTable 2.

Case Distance, D

D1 3m 0.6Ĥ

D2 5m 1Ĥ

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D3 8m 1.6Ĥ

D4 10m 2Ĥ

D5 15m 3Ĥ

Table 2: Distance Variable

2.2 Domain Geometry

The domain geometry is an important issue that must be considered carefully in modellingatmospheric wind flow. The domain must be large enough so that the atmospheric flow is notaffected by the domain to ensure the wind flows naturally as in real atmospheric condition.Another important issue that must be address in determining the domain’s length is to ensurethat the flow is fully developed before it hits the buildings as well as after it passes throughthe buildings (Mertens, 2006) . This ensures that the wake property and reattachment lengthcan be fully captured.

Figure 2: Domain Dimension

Figure 2 shows the domain dimension applied to simulate atmospheric wind flow for themodelled buildings configuration. The length is chosen to ensure that the flow is fullydeveloped before it passes the buildings and is fully developed after the flow leaves the outlet.

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Figure 3: Inlet Domain

Figure 4: Outlet Domain

Figure 3 shows that the velocity profile does not change before the wind flow pass throughthe buildings. This indicates the inlet is positioned far enough to ensure a fully developedwind profile. Figure 4 shows that velocity profile no longer change before and after leavingthe outlet. This signifies that the outlet position is sufficient to capture the wake regionproperty. Thus the computational domain is acceptable.

Fully developed velocity profilesbefore the wind flow passes thebuilding

Fully developed turbulentvelocity profiles after outlet

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Figure 5: Named Selection

Figure 5 shows the named selection applied to the model domain.

2.3 Mesh Information

Mesh size is an important parameter that determines the accuracy of the simulationparticularly in modelling atmospheric wind flow. In this simulation, the mesh type consists oftetrahedral elements. The tetrahedral elements is generated automatically by ANSYS 14.5and it provides a more automatic solution but with the ability to control accuracy in criticalregion. Critical region in this study is considered as the area around the UB and IB buildings,specifically on the building rooftop, as this is where the wind turbine is likely to be installed.Conversely, a hexahedral mesh may provide a more accurate solution, but is more difficult togenerate. For the critical region, wall function is applied to the inflation layer.

Figure 6: Computational Domain Mesh

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Figure 6 shows an overview of the mesh for the computational domain.

Figure 7: Inflation Layers on Buildings and Grounds

Figure 7 shows the inflation layer applied on the buildings and ground. The first height of theinflation layer is calculated based on a standard wall function, using Y+ function. A standardwall function for turbulent region is given as Eqn. 1.In modelling atmospheric boundary layer,it should be noted that an additional expression must be added, which is for a fully-roughregime as defined in Eqn. 2. KS is the dimension of roughness element which is the equivalentsand diameter (Blocken, 2007). Meanwhile, KS+ is a value more than 90 for fully rough flowregimes. However, for this study, the roughness elements are modelled by constructing theblock elements of buildings with mean height. Thus, only a standard wall function will beused.

[Eqn. 1]

[Eqn.2]

The first layer height, Y1 is calculated using the expression given in Eqn. 3. In this study, theRe number is chosen as . The Y+ value for this calculation is taken as 217, defining that it isa turbulent flow. The characteristic length, L is taken as the highest building height, which is30m. From the calculation, Y1 value is obtained as 0.15m.

[Eqn.3]

Min Size 0.10 mMax Face Size 20.0 mMax Size 20.0 mGrowth Rate 1.2 m

Table 3: Mesh Sizing

Table 3 shows the mesh sizing details. Determining the appropriate mesh size for anatmospheric boundary layer proves to be a challenge as the domain is considerably large.

Inflation layer on buildings

Inflation layer on ground

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Thus, an element size which is considerably small may result a massive amount of elementsin the computational domain. This could potentially increase the computational time, thusreducing computational efficiency. A sound judgement must be made to find a compromisebetween accuracy and efficiency.

First layer height, Y1 0.15mMaximum layers 20Growth Rate 1.2

Table 4: Inflation Layer Details

Table 4 shows the inflation layer details. The quality of mesh after inflation layer applicationis checked based on the skewness detail of the entire mesh. Skewness is one of the primaryquality measures for a mesh. Skewness determines how close to ideal a face or cell is. Anideal element will have a skewness of 0, while the worst element will have a skewness of 1.The skewness is defined as in Eqn. 4.

[Eqn.4]

= the largest angle in the face or cell

= the smallest angle in the face or cell

= the angle for an equivalent face or cell (e.g. 60 for a triangle, 90for a square)

Table 5 shows the mesh skewness detail. The average mesh skewness is closer to 0,indicating that the mesh quality is reasonably good.

Min 2.23128334555955E-04Max 0.918042156244921Average 0.198314425598469Standard deviation 0.115966284838766

Table 5: Mesh Skewness Detail

Figure 8 shows the mesh skewness bar chart. An observation made from the figure is thatmajority of the elements have skewness within 0 to 0.5. This shows that the mesh skewness iscloser to an ideal element. For good quality mesh, the skewness must be less than 0.85.Highly skewed faces and cells are unacceptable because the equations being solved assumethat the cells are relatively equilateral/equiangular.

In 3D, most cells should be good or better, but a small percentage will generally be in the fairrange and these are usually a few poor cells.

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Figure 8: Mesh Skewness Bar Chart

Table 6 shows the aspect ratio detail for the elements. The aspect ratio is the ratio of longestedge length to the shortest edge length. The aspect ratio for an ideal equilateral triangle or asquare is 1. From Figure 9, it can be seen that the average aspect ratio for the elements areapproximately 5.44, which is still considered far from the ideal aspect ratio of 1. This can beimproved by having a structured hexahedral mesh.

Min 1.1649Max 46.737Average 5.43685288664413Standard deviation 5.23338435156265

Table 6: Aspect Ratio Detail

Figure 9: Aspect Ratio Bar Chart

Mesh refinement is performed on the basis of a sensitivity analysis on the number ofelements. This ensures that grid-independency of the result. Four different face sizes areapplied to check for grid independency. The velocity is measured at two heights which are2m and 10m, above the installation building near the upwind corner. As the velocitystabilizes, the analysis is considered to be grid independent. Based on examination of Chart 1,face sizing of 2.5m is chosen and is regarded as the best compromise between accuracy andcomputational efforts. The velocity at both 2m and 10m no longer change drastically atfurther reduction of face size after 2.5m.

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Chart 1: Mesh Refinement

2.4 Setup

Modelling atmospheric boundary flows require suitable boundary conditions for the fluiddomain. The location of boundary conditions is shown in Figure 10. Information on thedomain fluid properties is stated in Table 8.

Figure 10: Location of boundary conditions

Material Air at 25°C

Heat Transfer NoneTurbulence K EpsilonDensity 1.185 kgm-3

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Dynamic Viscosity 1.831E-05 kgm-1s-1Table 8: Fluid Model Properties

Name BoundaryType Location Boundary Details

inlet Inlet inlet

Velocity profileTurbulence K EpsilonTurb. Kinetic EnergyTurb. EddyDissipation

ground Wall ground Wall roughness m

farfield Opening sky & side planeMass & Momentum EntrainmentTurbulence Zero GradientFlow Regime Subsonic

outlet Outlet outlet Average StaticPressure

0 Pa

symm Symmetry symmplanebuildings Wall buildings Wall roughness m

Table 9: Boundary Condition Details

0.51 m/s0.415m0.29m0.09200m

Table 10: Constants definition

Table 9 shows the boundary condition details applied to each named selection. Table 10 givesthe definition of constants used in the boundary condition equations. The pressure-velocitycoupling was made with the SIMPLE algorithm and the convergence to the final steady-statewas assessed with target residuals of 1 X 10-4. The simulation were based on a k epsilon twoequation turbulence model as this approach is widely used to computationally modelatmospheric boundary layer based on literature review. In this simulation, heat transfer isassumed negligible, as it is in real atmospheric condition.

Specific attention was given to the inlet boundary conditions, as this is the major source ofatmospheric wind flow characteristic within the computational domain. The velocity profilein this case is a function as given in Eqn. 5.

[Eqn. 5]

From the expression, it can be seen that the velocity is a logarithmic function of height. Inthis study, wind velocity measured at La Trobe University has been used to construct thevelocity profile as shown in Chart 2. The important thing to note from this velocity profile is

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it begins at an elevated height above the ground. A sub urban wind velocity profile startsabove the mean height of surrounding buildings, depending on site location. A frictionvelocity, which is , is 0.51m/s, dependent on site location as well. The wind velocity can bemodelled as a fully developed flow by utilizing the logarithmic function.

Chart 2: Wind Velocity Profile

Another important parameter to be considered for the inlet boundary condition is theturbulent kinetic energy and turbulent dissipation rate. Both parameters are modelled as afunction of height as given in Eqn. 6 and Eqn. 7.

[Eqn. 6]

[Eqn.7]

The turbulence intensity is given in Eqn. 8.

[Eqn. 8]

Turbulence intensity in atmospheric boundary layer decreases as height increases. Identifyingthe turbulence intensity for positioning wind turbine is important to analyse the energyefficiency.

3.0 RESULTS AND DISCUSSION

Logarithmic function of windvelocity profile begins at anelevated height; assumed to bethe mean height of surroundingbuildings based on specific sitelocation

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3.1 Validation

A validation of this setup is done against wind velocity results from a paper published in thejournal of Renewable Energy titled Microeolic turbines in the built environment: Influence ofthe installation site on the potential energy yield. Validation step is essential in all CFDsimulation to check and minimize error that is produced. Validation may be done againstexperimental data or established simulation results.

Chart 3: Validation with Journal

Chart 3 shows the results comparison between journal and simulation performed. In thispaper, the analysis is done for various upwind building heights, and the effect on wind flowacceleration is recorded. The velocity variation, is the difference between velocity measuredat 2m above the upwind corner of the installation building and free stream velocity at thesame height. It should be noted that the analysis is done in 2D. The exact buildingsconfiguration has been modelled for validation purposes. From the results, it can be seen thatthe velocity variation is comparable, as all the percentage difference is below 20%. Thereason for the difference may be due to the different turbulent kinetic energy function used.

3.2 Comparison between 2D and 3D flow

The 2D simulation is performed by setting up the width of the building to be much longer.This eliminates the effect of flow travelling around the building, and the flow is restricted toflow over the building only. In 3D, the flow will travel around the sides of the building as

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well, which means that the flow will face less resistance in a 3D simulation with the samesetup. As a result, the flow velocities on top of the buildings in 2D simulation are overpredicted. The 3D simulation allows the flow to travel in all directions after stagnating on thebuilding front face. The 3D analysis also captures vortices that occur in the z-axis which alsoaffect the flow behaviour.

Chart 4: 2D and 3D Result Comparison

Chart 4 is an extended version of Chart 3, showing result comparison between 2D and 3Dsimulation. It can be seen that the results is similar in trend, but is offset to a further decreasein velocity variation. The velocity on top of the installation building is further decreased, asthe flow mass now also travels around the building.

3.3 Y+ Contour Plots

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Figure 11: Y+ Contour Plots

Figure 11 shows the Y+ contour plots for the buildings. The Y+ value is defined as the non-dimensionless distance from the wall to the first mesh element, normalized by viscosity andvelocity. In order to produce accurate results, Y+ values should not fall in the buffer layer,which is in between 5 to 30. The buffer layer is an undesirable region, as neither thelogarithmic nor linear law functions govern the wall function.

Y+ value below 5 involves viscous laminar sublayer of the boundary layer to affect the flowacross the wall. Y+ values above 30 are ideal for modelling turbulent flows near the wallboundary, where the inertial forces are more domineering than viscous forces. The Y+ can bedescribed using Eqn. 9, where Y1 is the first element near the wall height, u* is the frictionvelocity and is the viscosity.

[Eqn.9]

A high Y+ value occurs at high friction velocity. From Figure 9, it can be seen that the Y+value is high at the front facade of the building. This can demonstrate that the flow velocity isrelatively higher in this region, proving that there is an accelerating effect of the wind.Observing the rooftop area, it can be seen that there are two spots of dark blue region near thecentre. This is due to the low velocity region, where the recirculating flow from separationphenomena reattaches.

3.4 Pressure Contour Plots

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Figure 12: Pressure Contour Plots

Figure 12 shows the pressure contour plots on the buildings. As the wind flow hits theinstallation building, it will be separated into four different streams. The first stream isdeviated over the building, the second stream is deviated down the windward facade and theother two streams deviate to the two sides of the building (Abohela, 2012) . The point ofdeviation is known as the stagnation point. The stagnation point is a point of maximumpressure, marked by red colour at the windward building facade in the pressure contour plots.The pressure is slightly lower at areas surrounding the stagnation point. This results inpressure gradient that pushes the flow to accelerate over the building, which is the desiredphenomenon for installing rooftop wind turbines.

The flow travelling along the windward facade will then separates at the edge of the building.This separation creates a wake area on the rooftop of the building. An adverse pressuregradient will push the flow backwards towards the low pressure wake region, creating arecirculation flow on top of the building.

3.5 Velocity Contour Plots

Pressure Contour regionon Installation Building

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Figure 13: Velocity Contour Plots (a) Overall (b) Close-up

Figure 13 shows the velocity contour plots for overall domain as well as a close-up view.From the overall view, it is possible to see the effect of having velocity wind velocity profilein the set up. This shows a typical wind velocity gradient in the atmosphere, as the heightincreases, an increase in wind velocity can be obtained. Thus, it is desired to place windturbines at an elevated height, to exploit high wind velocity and thus, generating more energy.However, it should also be noted that the velocity profile is dependent on different terrainsbased on Figure 14. This study intends to focus more on the sub urban terrain.

(a)

(b)

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Figure 14: Velocity Profiles for different terrain

An important observation that can be made from this velocity contours is a comparisonbetween the free stream velocity and velocity located on the rooftop at the same height. Fromthis, it is possible to make an early judgement on the accelerating effects induced by thebuildings in urban configuration.

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3.6 Velocity Vector Plots

Figure 15: Velocity Vector (a) Overall (b) Close-up

Figure 15 shows the velocity vector plots for the overall domain as well as a close-up view.From the overall view, it can be seen that the air flow generally separates at the edges of eachbuilding, creating a recirculation zone behind every building blocks. However, thereattachment length depends on the height of each building. The air flowing downwards thebuilding facade also creates a standing vortex. It can be clearly seen that a high velocitygradient exist at the separation corner, and this area is called the shear layer. A single rotatingvortex can also be seen in the canyon between the roughness elements.

As the flow travels along the windward facade, the velocity builds up, as a result ofconvective acceleration. Thus, it is possible to achieve a high wind velocity at the edge of thebuilding. This high velocity region can be exploited using wind turbine, to generate energy.However, another interesting parameter that must be examined is the skew angle of theapproaching flow.

(a)

(b)

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Figure 16: Skew Angle

Figure 16 illustrates the skew angle. The skew angle is the angle between wind flow and thebuilding rooftop. In this study, the wind flow is taken 3m height above the edge of therooftop. This height is taken as it is a typical height for an urban wind turbine. The skewangle may influence the efficiency of wind turbine in harvesting wind energy.

Skew Angle

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3.7 Streamline Plots

Figure 17: Streamline Plots (a) Isometric View (b) Top view

Figure 17 shows the streamline plots around the building in isometric and top view. It shouldbe noted that the velocity vector plots is highly dependent on the mesh density as eachprotruding vectors correlates to the local velocities at each node. However, the streamlineplots can clearly show the recirculation without depending on a fine mesh density as thepoints are connected to form a streamline.

From the top view, it is evident to see the flow separation as it passes the side edge of thebuildings. A high velocity gradient can be observed as well at this separation region. Theflow from both sides travels and creates a horse shoe vortex behind the building.

(a)

(b)

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3.8 Turbulent Kinetic Energy Contour Plot

Figure 18: Turbulent Kinetic Energy Contour Plot

Figure 18 shows the turbulent kinetic energy contour plots surrounding the buildings. Ageneral observation that can be made is that the turbulent kinetic energy increases within thevicinity of the buildings. The turbulent kinetic energy, as well as the turbulence intensities isan important parameter to study in positioning urban wind turbines, as it influences theturbines’ efficiency.

The maximum turbulent kinetic energy is located at the windward facade, approaching therooftop edge of the building as shown in yellow. This region seems to have high mixture anddiffusion of momentum. Further downstream, it can be seen that there is a reduction inturbulent kinetic energy as the energy is dissipated to surrounding. However, it should benoted that the standard k epsilon model tend show a more intense turbulent kinetic energybecause the dissipation of kinetic energy is smaller.

Figure 19 shows the turbulent kinetic energy contour starting from the wind ward facade ofthe building to the downstream facade. It can be seen that the turbulent intensities reduces asthe distance in x-axis increases on the building rooftop. The flow also becomes less turbulentas the height increases above the building rooftop. The black cross-point represents 3m abovethe rooftop, which is the designated height for wind turbine, for the purpose of this study.From observation, placing the wind turbine higher above the rooftop may result in higherenergy yield, as the flow is less turbulent. However, further analysis is needed for otherimportant parameters, such as the effect on buildings’ structural aspect of this designintegration.

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Figure 19: Turbulent Kinetic Energy Contours on Building Rooftop from wind ward facade to downstream facade

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Figure 20: High Turbulence Region

The edge of the building after separation results in high turbulence as shown in Figure 20.The high turbulence in and close to the separation bubble on the roof may reduce theefficiency of the turbine dramatically. Wind turbines placed in this region are also moreprone to damage caused by fatigue.

3.9 Reattachment Length

The reattachment length gives the point where the flow reattaches back to a surface afterseparation. The region before the flow reattaches is considered as the recirculation region.

Chart 5: Reattachment Length VS Distance

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Chart 5 shows the change in reattachment length values as the distance is increased. It shouldbe noted that the reattachment length is measured from the front facade of the installationbuilding. The flow reattaches later if the distance between two buildings is closer. Thisindicates that the flow is dominated by higher inertial force, pushing the flow forward. Thishigh inertial force may result from the accelerating effect produced by the existence of theupwind building at a closer distance.

3.10 Wind Velocities Comparison

In this study, five different distances between upwind building and installation building hasbeen simulated to see the effect on the wind velocities on the rooftop where the wind turbineis located. In order to deduce this effect, a comparison has been made between the velocitieson the rooftop and the free stream velocity at the same height for each distance cases.

Velocity Further Upstream [m/s] Velocity at 3m above IB [m/s] [%]5.69 5.86504 3.1445.69 5.87853 3.3885.68 5.76926 1.4965.68 5.79537 2.0315.68 5.83104 2.598

Table 11: Velocity Comparison

Table 11 shows the velocity comparison results. As can be seen, all cases gives an increase invelocity, thus provide evidence that upwind buildings can introduce acceleration effects onthe wind velocity.

Chart 6: Velocity Variation as a function of Distance

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Chart 6 shows the velocity variation as a function of distance between upwind building and

installation building. The highest ΔU recorded is 3.388%, with a distance of 5m. Further

increment actually resulted in a drop in acceleration, with the least ΔU recorded at distance of

8m. A deduction that can be made from this observation is that the flow is no longer affected

by the upwind building. From this point, as the distance is further increased, ΔU starts to

increase again. Further tests needs to be done to explore the flow characteristic at this extend.

It should be noted that the distance is considered to be between the back facade of the upwindbuilding and the front facade of the installation building. Another parameter that can beconsidered for future research is the effect of varying the length of the upwind building. Byvarying the length of the upwind building, the effect of angle on the velocity variation cannow be investigated. Figure 21 shows the location of angle . This study does not touch anyeffects caused by angle , but it represents an interesting remark for further research.

Figure 21: Angle Alpha

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4.0 CONCLUSION

This report has highlighted the CFD method of analysing atmospheric wind flow in a builtenvironment for the purpose of urban wind turbine installations. CFD proves to have manypotential in simulating the atmospheric boundary layer, and provides opportunities for windengineer to analyse flow characteristics, without the hassle and cost of performingexperimental as well as in-situ measurement. However, care must be taken to ensure thedegree of accuracy for this simulation by validating against existence data for wind velocities.A number of turbulence models are deemed to accurately model the atmospheric boundarylayer, but in this study, the standard k epsilon model was chosen as it is commonly used bywind engineers to provide an accurate result and saves computational time. The boundaryconditions in this study include a velocity profile function. The turbulent kinetic energy wasalso set up as a function of height. Constructing mesh for the domain proves to be a challenge,as the domain is relatively large, and a first layer height for mesh adjacent to the wall willresult in a large number of cells which could reduce the computational efficiency. The resultsshows that varying the distance between the two buildings have effects on a number ofparameters, including the flow velocities, reattachment length as well as skew angle.However, further research is needed to refine the results, by introducing more distancevariables. Apart from that, different turbulence model can be used to analyse the accuracy ofthe solution. This includes realizable k epsilon, SST and Large Eddy Simulation. A structuredmesh can also be constructed, which may produce a more accurate result. This reportprovides a fundamental understanding on wind energy analysis using CFD method, but toaccurately model and analyse atmospheric boundary layer requires a higher degree ofknowledge and understanding.

5.0 BIBLIOGRAPHY

Abohela, I. (2012). Effect of roof shape, wind direction, building height and urbanconfiguration on the energy yield and positioning of roof mounted wind turbines. RenewableEnergy , 1106-1118.

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Balduzzi, F. (2012). Microeolic turbines in the built environment: Influence of the installationsite on the potential energy yield. Renewable Energy , 163-174.

Blocken, B. (2007). CFD simulation of the atmospheric boundary layer: Wall functionproblems. Atmospheric Environment , 238-252.

Mertens, S. (2006). Wind Energy in the Built Environment. Essex: Multi-Science.