WIND FARM DESIGN AND

OPTIMIZATION

Harout Charoian Mini-Project at National Technical University of Athens

Date: 05/13/2016

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Table of Contents Abstract: ........................................................................................................................................................ 2

Wakes: ........................................................................................................................................................... 3

Wake Models: ............................................................................................................................................... 4

Wake Effects: ................................................................................................................................................ 5

Wake effects in wind farms: ..................................................................................................................... 5

Wind Farm Shadowing: ............................................................................................................................. 6

Optimization: ................................................................................................................................................ 7

Wind Farm Layout Optimization: .............................................................................................................. 7

Pitch Based Active Wake Control: ............................................................................................................. 8

Yaw Based Active Wake Control: .............................................................................................................. 9

Loads due to Yaw Misalignment: ............................................................................................................ 10

Conclusion: .................................................................................................................................................. 12

Bibliography: ............................................................................................................................................... 13

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Abstract:

The following report has been prepared for the 4th module of European Master in Renewable

Energy (2015/16) at the National Technical University of Athens specializing in Wind Energy.

The purpose of this project is to identify the importance of wake effects and ways of decreasing

wake effect losses.

Wind energy is one of the most mature technology in renewable energy industry. Due to its

success, many wind farms are being built with bigger sizes and number of turbines. Although the

technology itself is mature, there are still many studies especially on wakes to make wind farms

more efficient.

The wakes result of energy loss in wind farms, these wakes have to be minimized in order to make

wind energy more competitive. The energy market is being more and more competitive and the

additional losses through wakes are important to be analyzed and studied in order to have lower

cost of energy production and compete even better in the market.

This report provides an overview of different wake models and an explanation on how wakes are

created, its effects on a wind farm and also effects on neighboring wind farms. The report will also

discuss some optimization techniques that are used or under study to minimize wake effect losses.

The optimization that is recently introduced now is by de-rating the upstream wind turbine to

minimize the wakes for the downstream wind turbine. Another optimization which is still under

study is by yaw misalignment to deflect the wakes away from the downstream wind turbines. The

optimization techniques was concluded that it will increase the production of energy in wind farms,

but in the case of yaw misalignment technique more research has to be done on the fatigue loads

due to the misalignment.

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Wakes:

Wakes are created by the wind turbines due to the extraction of kinetic energy from the air. The

wakes happen downstream of a wind turbine, which illustrates that it does not create problems if

there was only one wind turbine, but many. In the case of many wind turbines, which is called a

wind farm, it is very difficult to avoid wakes from other turbines unless if you have one row of

wind turbines and a prevailing wind direction.

The Levelized Cost of Energy (LCOE) in a wind farm is reduced or increased significantly by the

change in velocity and the turbulence. The target of wind farm design is to maximize the energy

yield as a whole wind farm and minimizing the fatigue loading on wind turbines. The success of

every investment is measured by the profit and designing a good wind farm will play a major

contribution to the successfulness.

Wakes are important to be taken into account while doing a wind farm due to two main reasons,

one reason is that wakes are the effect of velocity deficit and this deficit is directly effecting the

production of the turbine by the third degree shown in the equation𝑃 =1

2∗ 𝜌 ∗ 𝐶𝑃 ∗ 𝑈

3 ∗ 𝐴. The

second reason to understand the significance of wakes in wind farms is that they have much higher

turbulences, these turbulences will have negative effect on the lifetime of the wind turbines due to

the increase of fatigue loads.

Figure 1: Velocity Deficit Model

In the figure above, it is shown how a wind turbine results in a velocity deficit with distance and

it is seen that the wake expands and gets larger with distance. It also suggests that the further away

you are from the turbine, the velocity deficit will recover and eventually turn to zero. This is the

reason why we don’t see turbines positioned right after each other.

In order to do these studies, it is important first to make some models which are very accurate to

real testing conditions. These models will then be used in trying to find the best wind farm lay-out

as well as the best way of using wind turbine control to maximize the wind farm.

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Wake Models: In order to prevent cases of very harmful wakes, some studies and researches were needed to be

done. Figure 1 looks simple to simulate but that’s only because it is a very simplified figure. In

reality, there are many conditions that need to be taken into account in order to have correlation

with real life scenarios. These conditions must be taken into account: the effect from the towers,

shear effect, rotation effect from the spinning blades, ground effects on the boundary layer and

turbulence from wind turbines and atmosphere. It is important to note that all these factors make

it very hard and complex to simulate perfect results. To simulate wake effects, there are two main

ways: the simple engineering models and the 3D models.

In the simple engineering models, it uses simplified momentum equations and mass conservation

equations to predict wakes, these are simple models which do not take into account the terrain

(ground effect) and the atmospheric boundary layer. Due to the simplicity of these concepts

calibrations is needed through experimental data to have close results. These simple engineering

models are based Prandtl, GCL semi-empirical and Abramovich’s theory for jets which could be

corresponded to wakes. The simple engineering models are not valid for near wakes and are only

valid for flat terrain and they also need calibration with experimental data.

There are more complicated but more accurate models which are the 3D models being used in the

industry. They are very difficult because it is hard to simulate turbulence and you have the

interaction of two different turbulences, the atmospheric turbulence and the turbulence that is

caused by the wind turbines. Due to the development of super computers it is now possible to run

full 3D Navier-Stokes equation simulations of wind farms, Reynolds Averaged Navier-Stokes

(RANS) have been used for the last 2 decades and having enough experience in applications. There

are two models in defining the Reynolds stresses for the eddy viscosity; the k-ε and the k-ω

turbulence models. Both of which need to be calibrated because the closure coefficients in them

are the numbers that are obtained through wind tunnel testing, these numbers change sometimes

in real conditions and that is the reason for the calibration. These models are now models that

could be used for the site to approximate wind and wake effect. But, there should be other models

to model the wind turbines that will be placed in the sites. The wind turbine modeling has been

done using two main techniques, the actuator disk concept and the actuator line concept.

There are two different ways of applying the actuator disk concept. The first way is that the loading

is considered to be uniform over the rotor disk, it is used widely due to its easy application and the

fact that only the thrust coefficient curve is needed. While the second way is that the loading is

variably distributed over the rotor disk, the thrust coefficient is also needed but this time along the

span to make the variable loading and it could be also done by using the Blade Element Theory.

For the both concepts there’s also the need of reference velocity; it is the velocity of the wind

before the velocity deficit happens due to the extraction of energy. To get the reference velocity,

the induction factor concept could be used. The second way of modeling a wind turbine is the

actuator line approach, Blade Element Theory is used to calculate the aerodynamic forces and

distribution the Gaussian distribution of forces are calculated by radial distances away. By having

these models all working together, it is possible to do many tests in improving the lay-out of the

wind farm and using wind turbine control techniques.

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Wake Effects: Wake effects in wind farms:

Now that there are the tools to model simulations with good precision, the effect of the wakes

could be simulated. The wakes depend on many factors such as: the stability of the atmosphere,

stability of wakes (meandering, turbulence), the turbulence intensity and distances between wind

turbines. If the site has a high turbulence intensity then the recovery of the velocity deficit will be

in less distances due to more “turbulence mixing” happening with the atmospheric boundary layer.

Usually, the turbulence intensity of offshore is much lower than the turbulence intensity of onshore

sites. Thus the distances between wind turbines are greater on offshore.

The figure below has been has been simulated by Torbon J. Larsen (Riso-DTU) and it shows how

the intensity of ambient turbulence has effect on wake effects and production of the wind farm.

Figure 2: Shows a wind farm distribution with a 5x5 grid and a spacing of 8D

In figure 2 it is shown the wake effect of different turbulence intensities on the left side shows the

ambient turbulence intensity of 1% and on the right side with a turbulence intensity of 10%. The

total power output is shown for wind speeds of 8m/s and all directions, and the decrease by just

having the turbulence intensity difference is huge. The wind farm with 1% turbulence intensity is

producing 20MW and 60MW was produced if the turbulence intensity was 9% instead. The losses

were three times more with the same wind farm layout!

Figure 3: Is taken by measurements from a Danish offshore wind farms.

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Figure 3 represents an unstable atmosphere on the left side and a stable atmosphere on the right

side in a Danish offshore wind farm which revealed a significant dependence of the atmospheric

stability on the wake losses. As seen in the figure there is the double amount of wake losses if the

atmosphere is stable rather than being unstable.

The stability of the atmosphere and the turbulence intensity of the wind has a very huge impact on

the energy production, but these effects are something that we cannot control and if there is

something that is not controllable then it cannot be improved as well. Two things could be done in

order to improve the output of the wind farm. Either by trying different lay-out arrays or use wind

turbine control option to maximize the output.

Wind Farm Shadowing:

Big wind farms cause velocity deficit downwind the farm, this is due to the wakes that we have

discussed before. Studies have shown now that due to increasing number of wind farms some wind

farms are being developed either upstream or downstream the wind farms causing them to be in

the wakes of the other wind farm. This effect is called also wind farm shadowing.

Figure 4: Wind speed effect due to neighboring wind farms (RisoDTU)

Figure 4 represents the velocity deficit due to a neighboring wind farm, it is seen that the deficit

starts as soon as the wind enters the first wind farm and recovery of the wind starts as soon as it

leaves the wind farm. But the downstream wind farm sees lower wind speed because it has not

fully recovered from the wakes of the neighboring wind turbines. This is a major challenge to

advance in which raises questions to the policies of offshore wind farms especially. Offshore wind

has usually a low turbulence intensity and also its flat terrain makes a slow recovery of wakes

between wind turbines. Thus, larger area is need for the wakes to recover and the velocity deficit

to recover as well. The challenge in the policy is how far should a new wind farm be located away

from the older wind farm for them not to have wind farm shadowing, according to (RisoDTU,

2007) the recovery of the wind deficit between wind farms are between 30-60km. The distance of

the recovery depends on the ambient turbulence, the stability of the atmosphere and the number of

turbines in the wind farm. The smaller the wind turbine groups then the reduction of the wind

speed is less.

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Optimization: Wind Farm Layout Optimization:

The effects of wind turbine wakes sometimes even decrease the energy production by 50%, and

this is not a small number, this is the difference between making your project liable or a huge

failure. To optimize the design of a wind farm there are some software already available in the

market such as WindFarmer. The WindFarmer optimizes the wind farm while taking into account

restrictions such as the reachability, slopes, cabling and much more if needed. It takes into account

the wind directions and with the restrictions given, it does iterations with random places for each

wind turbine within the boundaries and gives us the best locations for the wind turbines.

Figure 5: Represents the difference between not optimized and optimized wind farms (TUDelft)

Figure 5 shows us the difference between a not optimized and optimized wind farm. On the right

is the optimized wind farm and on the left is a regular wind farm with no optimization at all. The

optimization was done without the restriction of cable costs, and it has increased the production of

energy but due to the cabling costs and longer routs it was not a liable investment thus another

restriction was added to have more real solution.

In figure 6, below it is seen that there has been put some restrictions that the wind turbines cannot

move further than a certain location from its original space, this is to minimize the cabling costs

and at the same time optimizing the wind farm.

Figure 6: Optimized wind farm lay-out (TUDelft)

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The different colors in figure 6 show us two iterations of optimization and the green color is the

original place of the wind turbines without any optimization. These optimizations have been put

to practice now in a more serious matter in the offshore wind farms due to the flat terrains and less

ambient turbulence which wakes are penetrating more in wind farms than on complex terrains

onshore.

Pitch Based Active Wake Control:

Other ways to increase the energy output of the wind farm is by wind turbine control techniques.

There are two different kinds of wind turbine control. These wind farm optimization techniques

are regularly used to put wind turbines closer together thus decreasing the electrical infrastructure

costs or if the wind farm already exists but optimization was needed. The first method is by de-

rating the upstream wind turbine by using the pitch control of the system and making the wind

turbine more transparent for the wind turbine.

Figure 7: The velocity deficit by two systems (ECN)

In figure 7, it shows on the left hand side that the operation of the upstream wind turbine is on full

production and the velocity deficit downstream causes much less wind speed to reach the second

turbine due to the wakes. On the right hand, it is shown that by de-rating the upstream wind turbine

the velocity deficit is much less for the second turbine since there would be less wake effects. It

might seem that both wind farms would produce the same amount of energy due to the same

positioning, wind speed and direction. But, in practice the main idea is to compensate the losses

of the de-rated wind turbine by the downstream wind turbine and in most cases it the de-rating of

the wind turbine by just a small amount could up-rate the downstream wind turbine by more. De-

rating the wind turbine upstream will also have positive effect on the downstream wind turbines

since it will decrease the turbulence intensity thus less fatigue loads for the wind turbines. ECN

has done some research on Nordsee Ost wind farm layout, by using FarmFlow software, on the

maximization of the wind farm power production as well as measuring the ‘damage equivalent

loads’. The experiment was concluded with a 3.3% more power production and in some cases

reduction of damage equivalent loads of 40%, (Brand, Bot, Kanev, Savenije, & Ozdemir, 2014).

The increase of AEP 3.3% might not seem much, but these kind of increases add up to make the

industry more competitive. Also looking at the reduction of the fatigue loads has direct effects by

making the system needing less O&M.

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As a summary de-rating wind turbines upstream will increase the power production of the wind

farm and in the meantime decrease the loading.

Yaw Based Active Wake Control:

The second way to use wind turbine control in optimizing the wind farm is by setting the turbine

misaligned with the wind direction, which is called yaw misalignment. It is misaligned mainly to

divert the wakes away from the downstream wind turbines. Unlike the de-rating of the wind

turbines the yaw misalignment will increase the loads on the system thus very careful operation

has to be done in order the wind turbine not to be performed more than its designed limit.

Figure 8: Diverging wakes by the method of Yaw-Misalignment

Figure 8 shows a simple visual example on how yaw misalignment could diverge the wakes for

the downstream wind turbine. The yaw misalignment technique has higher potential than the de-

rating of the wind turbine method because the wakes are being directed away rather than being

reduced. Diverging the wake would mean that the downstream wind turbine would get most of its

wind from the undisturbed wind flow rather than having the wake of the one upstream. The

disadvantage of the yaw misalignment method compared to the de-rated power is that it is only

beneficial for only two wind turbines in a row compared to the de-rated power technique it is

possible to do it for more than three turbines in a row.

The same simulation has been done by ECN with the same Nordsee Ost wind farm layout and it

is interesting to see that the production has of the top row has increased by 17.4%. Since the wakes

could only be diverted for the two turbines in a row that is the reason why the top row as been

measured. 17.4% increase by yaw misalignment compared to 3.3% due to de-rating is a huge

difference; however, the big increase will also have big impacts on the fatigue loading of the

turbine. The effect of yaw misalignment in downstream wind turbines should also be studied. I

have stated that it will decrease the fatigue loading of the downstream wind turbines since they

operate outside the wakes. But what if the downstream wind turbines operate in half-wake

operations? The fatigue loading on the downstream wind turbine increase due two reasons, one

reason is that the wind speed is faster than being in the wakes and the second reason is that

sometimes operation in half-wake makes asymmetry in loading which causes tremendous amount

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of fatigue loading on the turbines. This topic is yet to be studied more in depth, but the results of

researches that are already available show positive signs that using yaw-misalignment technique

will cause considerable amount of power production increase in the expense of fatigue loads on

some turbines.

Loads due to Yaw Misalignment:

In order to prove if yaw misalignment has any effects on loading, using hGAST a script provided

by National Technical University of Athens, I have experimented two cases of loading. The first

case that was experimented is the loads during normal operation and the second case with 20

degree yaw misalignment. In both cases the simulations were identical, the wind turbine was a

5MW, 126 meters diameter, 89.5 meters tower height and under perfect wind conditions (no

turbulence or shear) with 9m/s wind speed. By applying these in the hGAST script, I have looked

at the forces on the tower and blades. The graphs are shown below:

Figure 9: The graph above show ‘pitching’ moment on the root of the tower

In figure 9, the ‘tilt’ moment causes the tower to move forward and backward oscillation due to

the thrust. The purple line is the loads with perfect alignment with the wind and it is seen that the

oscillations compared to the one with misalignment has higher amplitude. The high amplitude

directly effects the fatigue loading thus proving us that misalignment has more fatigue loading

than the one with perfect alignment. Another explanation could be seen through the two plots, is

that the misalignment has less average force compared to the normal operating turbine. This could

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be explained that the thrust of the normal operating is more and it is extracting more kinetic energy

from the wind.

Figure 10: The graph represent the ‘roll’ moment on the tower

Figure 10 shows the two case of turbines, the graph represents the ‘roll’ moment which causes the

tower to oscillate sideways. In the chart it is seen that the average for the misaligned is also less

compared to the normal operating one, this load is mainly due to the generator torque. The torque

for the misaligned is less because it does not capture as much energy as the normal operating wind

turbine thus having lower average loads. But looking at the amplitudes of the two cases, the

misaligned wind turbine has higher amplitudes and this causes more fatigue loads.

The main factors of fatigue loading is the number of cycles and its amplitudes. In both cases the

number of cycles were the same for both tested turbines. But, the amplitudes of the loads were

higher when the turbines were misaligned compared to the normal operating turbines. This

suggests that misalignment technique does put extra fatigue loadings on the towers especially

during low operational wind speeds. This leads us to a conclusion that the fatigue loads are effected

by the yaw misalignment and at higher wind speeds there will also be bigger impacts since the

amplitudes will be much more.

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Conclusion:

The importance of wakes to make the wind turbines more competitive in the market is undeniable.

Due to the wakes and bad positioning of wind turbines it is possible for some businesses to fail if

the wakes are not considered or taken seriously. Due to the effects on production it is very difficult

to find wind farms that agree to do experiments on them and there are only few wind farms built

to study wake effects because of its high investment costs. Instead, many models have been built

to simulate the wakes instead of using real wind farms. The models were discussed which were

from simple engineering models to complex models such as Navier Stokes models.

The effects of wakes depend on many factors, such as the ambient turbulence, the stability of the

atmosphere, the turbulences created due to upstream wind turbines and the distances between wind

turbines. The ambient turbulence and the stability of the atmosphere are natural phenomenon

which engineers can’t do anything about it. But, in order to have the most output out of the natural

conditions there are many ways to optimize the wind farms.

The first optimization that was discussed was having a better lay-out configuration depending on

the wind direction and minimizing the wake losses with some optimization programs such as

WindFarmer. Other ways optimizing wind farms were discussed as well, which is by the use of

the control systems on the wind turbine. There are two types of wind turbine control techniques:

the pitch based active wake control and yaw based active wake control. The pitch based active

wake control is already used commercially with positive results which decreases the fatigue loads

for the downstream wind turbines as well as increasing their production by de-rating the upstream

wind turbine and results in producing less wakes. The second technique is still not used

commercially and is under study, it was resulted that there is huge potential in the increase of

power production in this technique but there are also some concerns about the fatigue loadings and

the probability of having loads more than its designed capability. A simple simulated model was

run to see the difference on the loads of the tower if it has been misaligned by 20 degrees. In both

graphs in figure 9 & 10, suggest higher amplitudes of moment forces will happen which will result

in more vibrations and more fatigue loads. More research needs to be done also to see if these

fatigue loads are compensated by the production boost and to make this technique also

commercially applied.

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