Design of PVC Bladed Horizontal Axis Wind Turbine for Low Wind Speed Region
AES Barna Wind Turbine Provisional Fiday
1. College of Engineering & Informatics
Assignment Submission Page
Student/Group Name(s): Student(s) ID Number:
Justin Conboy 10101683
Cathal Power 11413242
Joe Geraghty 10403221
Class and Year: 4th
Year Energy Systems Eng. (Mech)
Subject Code and Name: (eg ME117 CADD) GE400 Advanced Energy Systems
Lecturer Name: Dr. Rory Monaghan
Title of Assignment: Major Project: Leitir Gungaid Wind Farm
Submission Deadline 19th
November 2014
Submission Date:
Deduction imposed by Staff for late submission See Blackboard
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from anywhere without giving a reference to the source. Sources include the internet, other
students’ work, books, journal articles, etc.
You must ensure that you have read the University Regulations relating to plagiarism, which
can be found on the NUIG website: http://www.nuigalway.ie/engineering/plagiarism/
I have read and understood the University Code of Practice on plagiarism and
confirm that the content of this document is my own work and has not been
plagiarised.
Student’s signature
Justin Conboy
Cathal Power
Joe Geraghty
3. 1. Introduction:
Leitir Gungaid Wind Farm is an array of wind turbines in Barna, Galway. The wind farm consists of 17
simular turbines but there are 3 different turbine power output-ratings between the 17. There are seven 3
Megawatt (MW) turbines, six 2.3 MW turbines and four 2 MW turbines on location at Leitir Gungaid Wind
Farm (Barna Wind Farm).
The farm was comissioned in March of 2014 and is Irelands newest wind farm. It is already fully
operational, but had caused quite a lot of contraversy with neigbours over the planning process. The main
concerns for residents were, noise, light flicker, and obstruction of cenery.
2. Project Objectives:
Our obective is to model the 17 wind turbines in Barna Galway, to model the power output of each
tubine blade and, in-turn, each of the 3 types of individual turbine.
Also, to show the construction cost of the wind turbines and, using real time data and current
energy prices, to calculate the income produced by the turbines. We will show, for wind turbines in large
scale electricty production, the spacing between turbines.
Our project involves carrying out a “Matlab-Simulink” evaluation of the wind turbines at Barna,
Galway. The evaluation will take wind data from the previous year to present date in minutes. This data will
be applied to a Matlab replica model of the turbines. The blade profile of each of turbine is identical, but
each turbine will have a different make up, different torsional rating and different tip speed ratio. The
Matlab simulation will calculate the electricity produced by the wind turbine array using only the blade
configuration from the NACA database. This will give the value of energy produced in Euros at the current
market price. A cost benefit analysis will be produced as part of the project to validate the cost of the
turbine array and its impact on the area.
A “Levelised Cost of Electricity” (LCoE) will be carried out also, so as to show the actual payback
time of the wind farm
4. 3. Turbines:
Enercon GmbH are based in Aurich in Germany. They
are one of the largest wind turbine manufacturer in the
world. Enercon has production facilities in Germany,
Brazil, India, Canada, Turkey, Sweeden and Portugal. In
recent years Enercon have set up their Irish
headquarters in Tralee, Co. Kerry, Ireland
The Turbines being uses at Barna are the
Enercon
Four: E-82 E2/2,000 kW
Six: E-82 E2/2,300 kW
Seven: E-82 E3/3,000 kW.
The Turbines are quite similar but have different sized
shafts and materials to transfer the different powers to
the generator.
Fig.1 Cross sectional drawing of nacelle E-82 E3.[1] Fig.2 The Enercon E-82 E3/3000 kW turbine.[2]
5. Rated power: 3,000 kW
Rotor diameter: 82 m
Hub height: 78 m / 85 m / 98 m / 108 m / 138 m
Wind class (IEC): IEC/NVN IA und IEC/NVN IIA
Turbine concept: Gearless, variable speed, single blade adjustment
Rotor:
Type: Upwind rotor with active pitch control
Rotational direction: Clockwise
No. of blades: 3
Swept area: 5,281 m²
Blade material: GRP (epoxy resin); integrated lightning protection
Rotational speed: variable, 6 - 18.5 rpm
Pitch control:
ENERCON single blade pitch system, one independent pitch system
per rotor blade with allocated emergency supply
Drive train with generator
Main bearing: Double-row tapered / cylindrical roller bearings
Generator: ENERCON direct-drive annular generator
Grid feeding: ENERCON inverter
Brake systems:
3 independent pitch control systems with emergency power supply,
rotor brake, rotor lock
Yaw control: Active via adjustment gears, load-dependent damping
Cut-out wind speed: 28 - 34 m/s (with ENERCON storm control)
Remote monitoring: ENERCON SCADA
Fig. 3 Data Table for the E82-E3
6. 3.1 Blade Design:
The blade we are simulating is a NACA 4412 blade. The blade twists along the axes of the blade length. The
twist is there to counter act the increase forces along the blade length as the radius of the blade increases
away from the main shaft of the turbine.
Fig. 4 NACA 4412, Drawn on Inventor Pro
The blade twist is designed to create and even force all the way along the blade so at to keep reduce
bending moments as the radius increases along the blade length.
Fig. 5 NACA 4412 with a 22.7 degree blade profile turning: Drawn with Inventor Pro.
7. Fig. 6 NACA 4412 Coefficient of Drag and Lift profile averages, compiled from NACA data online.
The NACA 4412 has a maximum coefficient of Lift of 1.6 at the 16 degree point. This is our relative wind
angle for maximum power at the shaft end of the blade. As the radius increases we will rotate the degrees
of the blade so that the force acting on the blade will decrease.
This decrease in lift force will be proportional to the radius of the blade. This will cause torque, ie. Lift force
multiplied by the radius, to be even all along the blade points. After adjusting the blade angle along the
blade for optimisation, we should have a steady force acting on the blade for the entire length.
4. Simulink Blade Simulation:
We have modelled the blade in 9 force sections with the 10 section being the shaft connector with no
force.
As can be seen from the representative model, the blade has been broken up into 9 sections. Each section
has a specific Pitch Angle. This is, again to evenly distribute the torque along the blade. We are only
modelling for 9 sections because this should be very sufficient to get a good overall view of the forces along
the blade.
The torques is all added up along the length of the blade and the sum is multiplied by 3. This is done simply
because there are 3 blades on each of the turbines.
The torque is then added and multiplied by the tip speed ratio to give the overall Power Output of the
turbine.
The resultant display at the far right of the model displays the total power output by the turbine.
8. Fig. 7 A Simulink model of the 3MW blade section run at full power. Not the 9 sections of the blade
Power Formula (Betz Power)
P = Nominal Power (W)
ρ = Density of Air (kg/m3)
A = Swept Area (m2)
V = Air Velocity(m/s)
BETZ POWER
V2/V1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
V1 9 9 9 9 9 9 9 9 9 9 9
V2 0 0.9 1.8 2.7 3.6 4.5 5.4 6.3 7.2 8.1 9
P/Po 0.5 0.5445 0.576 0.5915 0.588 0.5625 0.512 0.4335 0.324 0.1805 0
9. Graph 1. Power In/Power Output Optimisation.
Fig.8 Working of the calculations of the blade, the blades of the 2MW and 3MW turbine were calculated using the same process
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0 0.2 0.4 0.6 0.8 1 1.2
P/Po
P/Po
10. In order to calculate the power generated by the turbine we had to calculate the power generated
by each individual blade first. To do so we inputted the wind data given from the IRUSE, we then
implemented Betz Limit which says that the maximum power that can be extracted from the wind is 16/27
(0.593). This law was derived from the principal of conservation of mass and momentum of air flowing
through an actuator disk by Albert Betz in 1919. Figure 5 shows just how complex the calculation of the
power generated is factoring in all components of the blade.
Fig. 6 Displays the trigonometric function used in calculating the lift force
The trigonometric function shown above is a key component in calculating the lift force
experienced by the blade for an optimum relative wind angle. This function is child to its parent function
shown in fig. 5 which calculates the total power generated by the blade.
Fig 2. Derivation of Thrust and Torque Equations: Drawn on MS Paint by Justin Conboy
The lift and drag forces produced by the aerofoil do not act in the direction of the x-axis or the y-axis, these
forces must be decomposed into the components in the x and y direction. Once these components have
11. been found then the torque and axial thrust can be calculated provided the coefficients of lift and drag,
along with the platform area, are known. The green components of lift and drag are combined to provide
the torque and the red components are combined to provide the axial thrust.
Where is Torque , is Platform area (chord*section length), is Coefficient of lift, is
Coefficient of drag, is Angle of relative wind
Following from these equations one can see that the thrust force greatly increases as decreases. This is
the main reason for stipulating a low coefficient of lift for the tip profile as to attempt to decrease the axial
thrust.
4.1 Blade performance
The formulas used for these calculations are as follows:
= Lift/Drag force (N)
= air density (kg/m3)
= wind velocity (m/s)
= section coefficient of lift/drag
12. Figure X: Lift Force blade points E83-3MW-9
Graph X shows the lift at point E83-3MW-9. This is the 9th
calculated point of the blade and is at the tip end
of one of the 3MW turbine blades. It is located 41 meters towards the tip and the blade, has an angel of 7.3
degrees with a Relative wind angle of 1.397 degrees. The part can be seen as display 9 in the blade
summation block, below.
Figure X: Blade Summation Block
13. 5. Turbine Limiting Factors:
Figure 7: 3 MW limiting factor used to calculate turbine cut speeds and cut out speeds.
A limiting factor is what determines the cut in speeds and cut out speeds for a wind turbine. The
cut out speeds also known as the survival speeds of commercial wind turbines varies on the size of the
turbines. As the power in the wind increases as the cube of the wind speed, wind turbines must be built to
withstand much higher loads such as gale force winds. There is certain ways of reducing the torque in high
winds in order to protect the wind turbine. If the rated wind speed is exceeded the power generated has to
be limited. This can be done by implementing a control system that consists of, sensors to process
variables, actuators to manipulate energy capture and component loading and control algorithms to
coordinate the actuators based on the information gathered by the sensors. Also, the cut in speeds will vary
depending on the size of the wind turbines. Although the cut in wind speeds pose no threat to integrity of
the turbine itself it is important to have such a speed because you would be generating such small and
inconsistent amounts of power is would be wasteful with respect to wear & tear of the machine.
At Barna the cut in/out speeds for each differently sized turbine is different, for the 2MW wind
turbine no power is generated if the wind speed is below 1.2 m/s and power generation is limited if the
wind speed rises above 13 m/s. For the 2.3MW wind turbine no power is generated if the wind speed is
below 1.2 m/s and power generation is limited if the wind speed rises above 14 m/s. And lastly for the
3MW wind turbine no power is generated if the wind speed is below 1.2 m/s and power generation is
limited if the wind speed rises above 17 m/s. Therefore for each wind turbine a factor of safety has been
applied to the limiting speed in order to protect them and avoid accidents. There is an overall shut down
speed of 31 m/s applied to all the turbines. This is the maximum safety seed allowed. The blades turn to a
pitch angle of 0 lift and a break is applied.
An example can be seen in the graph below. The input speed into the 3MW turbine varies from 0 to
36 m/s in a two cycle example. What we should expect is that the turbine produces 0 lift from the 0 to 1.2
m/s cycle and gradually increase with power until it hits 17 m/s. At this point it the saturation should kick in
14. and the blade should only produce 17 m/s worth of lift even going from 17 m/s to 31 m/s. At the 31 m/s
stage the blade’s should produce 0 force as the wind turbine is now in shut down mode.
Figure X: Wind speed on top ranging from 0 to 36m/s over two cycles. Usable wind on graph below.
6. Complete Turbine Overview:
The representation below shows the process used in order to calculate the total turnover
generated by the turbines, it also shows the total power generated by the turbines along with the payback
period. Wind data from the area was read in from an excel file where a correctional gain optimises the data
to sync with the area, given the limiting factors for each turbine along with the blade geometry we could
sum the crucial information needed to estimate turnover given today’s energy prices, power and payback
period.
15. Fig.8 Displays the absolute power generated if the turbines operated at 100% capacity.
Fig.9 Displays each individual Turbine configuration.
The above representation displays how the blades for each turbine are configured, initially the
limiting factors for each turbine are set, these show how the turbines act above and below certain wind
speed. From there each of the turbines blade geometry calculates the power generated by each individual
model, this information is passed on to a multiplier where the total power generated by all of the turbines
is calculated and added allowing us to determine the turnover and payback period.
16. Fig. 10 Displays how energy prices, energy conversion and project costs are implemented to output the final results.
Fig. 11: Displays how the cost of the infrastructure was calculated.
Research on Barna showed that the infrastructure costs for each turbine was approximately
€100000 each, this infrastructure included foundations, cables and land costs. Using a simple multiplier of
17 the total number of turbines it allowed us to calculate total infrastructure cost, added to that the total
cost of the wind turbines was €40,000,000. We also established that the maintenance costs per turbine was
1.75% over a period of 11 years that calculated the total maintenance costs.
17. 7. Carbon Offset:
To calculate the complete carbon offset by the use of these turbines at Barna, it first needs to be
established the total power generated by the turbines over their entire lifespan. Each turbine is said to
have a lifespan of 20 – 25 years. At Barna it is said that each turbine should last a maximum of 25 years. To
calculate the carbon offset the following equation has been established:
(Annual Power Generated at Barna) x (Lifespan of the Turbines)x(C02 Emissions per fuel type)
= (kWh/y) x (No. of years) x ( gC02/kWh)
= gC02 offset by wind compared with different fuel types
Therefore the resultant of the above equation represents the amount of grams of C02 offset by the
production of clean electricity over the lifespan of all the wind turbines at Barna combined, (coloured in
yellow in the table below). In order to keep the numbers manageable it was converted back to tonnes of
C02 offset by the production of clean electricity over the lifespan of all the wind turbines at Barna
combined, (coloured in orange). The next task was to convert it back to the annual tonnes of C02 offset by
the 17 different turbines at Barna (coloured in green) as was specified at the beginning of the project.
Lastly it was required to show the C02 emissions offset per kWh (coloured in pink). To verify the results
shown below the average amount of C02 offset per turbine per year was estimated per fuel type and
compared with information from the Irish Wind Energy Association (coloured in purple).
Table. 1 Displays the Carbon offset at Barna from clean power generation when compared with
hydrocarbon forms of power generation.
To fully grasp the scale of the power generated at Barna, take a single 2.3MW wind turbine that will
produce approximately 5500MWh/y and a typical ‘A rated’ fridge freezer that consumes 408 kWh/y. That
single turbine could power (5,500,000/408 = 13479) fridges. Barna produces 112484312 kWh/y that would
amount to (112484312/408 = 275,697) fridge freezers for a year.
Fuel
Emissions per fuel
type (gC02/kWh)
Power at
Barna (kWh/y)
Lifespan
Overall Carbon
Offset (gC02)
Natural Gas 360 112484312 25 1.01236E+12
Fuel Oil 754 112484312 25 2.12033E+12
Coal 811 112484312 25 2.28062E+12
Peat 1119 112484312 25 3.14675E+12
Overall Carbon
Offset (tonnes)
Annual Offset
(tonnes)
Emissions offset
(tonnes C02/
kWh)
Average offset per
turbine per annum
1012358.808 50617.9404 0.001095727 2977.525906
2120329.281 106016.4641 0.002294938 6236.262591
2280619.426 114030.9713 0.002468429 6707.704193
3146748.628 157337.4314 0.003405884 9255.143024
18. 8. Levelised Cost of Electricity:
From the data obtained for system output a value for Levelised Cost of Electricity was calculated. A number
of parameters were entered which conform to calculated results and industry norms. The plants operating
life is twenty five years while a conservative estimate of 1.75% for maintenance is included in the
calculations. Initially a 1.75% rate did not seem to be that large but over the lifetime of the project this
amounts to €18,243,750 over the lifetime of the project.
The wind farms expected performance was also taken into account over its lifetime. This is known as the
degradation factor and reduces power output over the time period. Onshore wind farms performance can
be reduced by up to 16% over a twenty year period so an estimate of 1.5% per year was established.
Including this factor in calculations can increase the LCOE value by up to 9%. (ref1)
Two approaches were taken with regard to LCOE calculation. The first was assuming the investment costs
were paid up front and that finance was not needed for the project. The second was that a loan was
established to pay 90% of the total costs with the other 10% provided up front by the developer.
The second scenario is a much more realistic one as generally when a project is conceived, the developer
tries to find sources of investment to fund the project. This can entail approaching private investors or
entering in to a loan with a bank or other credit institution.
Loan repayments were spread out over the first ten years of the project with an interest rate of 3.0% which
is typical for a project of this proportion. These repayments were tabulated in excel along with
maintenance and other costs to produce a cumulative net cash flow chart.
Figure : shows revenue derived from electricity sold at the LCOE calculated of €.036 cents/Kwh. Capital
costs are also shown with construction in the first two years and production beginning in year 3.
Decommissioning costs of 5% were also included at the end of the 25 year life of the project.
-€23,000,000.00
-€18,000,000.00
-€13,000,000.00
-€8,000,000.00
-€3,000,000.00
€2,000,000.00
€7,000,000.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
Revenue/Expenditure
Revenue
Capital Cost
Expenditure
19. Figure : shows revenue derived from LCOE and loan repayments over a ten year period as opposed to full
capital outlay up front. Decommissioning costs are also shown again at a rate of 10% of initial investment.
From the figures analysed in the excel spreadsheet a value of .0399 cents was calculated which is derived
from scenario 2. This involves totalling all debt servicing and maintenance costs and taking values for
electricity produced with a degradation factor of 1.5% per year included. It should also be noted that this
accounts for an annual electricity escalation rate of 1.5% which again is in line with historic figures.
Figure : shows revenue received for selling electricity at the current rate of 9 cents per Kwh, with yearly
escalation of 1.5% included in calculations.
-€10,000,000.00
-€8,000,000.00
-€6,000,000.00
-€4,000,000.00
-€2,000,000.00
€0.00
€2,000,000.00
€4,000,000.00
€6,000,000.00
1 3 5 7 9 11 13 15 17 19 21 23 25
Revenue/expenditure
Expenditure
Revenue
-€10,000,000.00
-€5,000,000.00
€0.00
€5,000,000.00
€10,000,000.00
€15,000,000.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Revenue/Expenditure
Revenue
Expenditure
Decommissioning cost
20. Figure : shows net cumulative cash flow over the lifetime of the project. The cash flow is negative in the
opening years due to down payment costs. A noticeable decrease is observed after year 25 due to
decommissioning costs.
9. Area and Noise
This is a key factor in ensuring their safety, the space between each wind turbine is between 6 – 10 time
the rotor diameter depending on topography
10. Results:
Table 2 Displays, Accumulated Sales at €0.09 per kWh. Power Out (MW) and Wind Speeds (m/s).
-€10,000,000.00
-€5,000,000.00
€0.00
€5,000,000.00
€10,000,000.00
€15,000,000.00
€20,000,000.00
€25,000,000.00
1 3 5 7 9 11 13 15 17 19 21 23 25
Culumative Cash Flow
21. Wind Correction EXPLINATION
The wind data was split into 525104 minutes of wind speed information which was obtained from IRUSE[5].
The data was wind speed velocities from the start of October 2013 to the start of October 2014.
The reason why we added a correctional gain was to bring the wind speed from the data at hand up to the
wind speeds at the 70m elevated site at Barna.
The wind speed data was taken from weather station at NUI Galway which is located on the roof of The
Concourse. There are a huge amount of trees and buildings which reduce the wind speed before it gets to
the weather station.
During our research, we found that turbines in Galway are running at approximately 30% of maximum
capacity. With our wind data we found that we were hitting 32% less than the “30% of Maximum”.
We decided, for our project, to compensate for the 32% loss by adding a gain of 49.5%. This brought the
wind speed up to the “30% of Maximum”.
We tried to get wind data for the area, but this was considered a commercial secret. If wind speeds were
available for the exact area, we would simply set the correctional gain to 1.
Fig. 12 Displays the wind correctional gain multiplier.
22.
23. 0 1 2 3 4 5
Revenues
Power output (k/w/hr.) 1.29E+08 1.29E+08 1.29E+08 1.29E+08 1.29E+08
Avoided cost of electricity 0.0918 0.093636 0.09550872 0.097418894 0.099367272
Total Revenue €11,842,200.00 €12,079,044.00 €12,320,624.88 €12,567,037.38 €12,818,378.13
Expenditure
Initial Capital Expenditure €4,170,000.00
Amount financed €37,530,000.00
Total debt payment €4,556,028.00 €4,556,028.00 €4,556,028.00 €4,556,028.00 €4,556,028.00
Total maintenance costs €625,500.00 €625,500.00 €625,500.00 €625,500.00 €625,500.00
Total expenses €5,181,528.00 €5,181,528.00 €5,181,528.00 €5,181,528.00 €5,181,528.00
Net cash flow -€4,170,000.00 €6,660,672.00 €6,897,516.00 €7,139,096.88 €7,385,509.38 €7,636,850.13
Cumulative net cash flow -€4,170,000.00 €2,490,672.00 €13,558,188.00 €14,036,612.88 €14,524,606.26 €15,022,359.50
6 7 8 9 10
Revenues
Power output (k/w/hr) 1.29E+08 1.29E+08 1.29E+08 1.29E+08 1.29E+08
Avoided cost of electricity 0.101354618 0.10338171 0.105449344 0.107558331 0.109709498
Total Revenue €13,074,745.69 €13,336,240.60 €13,602,965.41 €13,875,024.72 €14,152,525.22
Expenditure
Initial Capital Expenditure
Amount financed
Total debt payment €4,556,028.00 €4,556,028.00 €4,556,028.00 €4,556,028.00 €4,556,028.00
Total maintenance costs €625,500.00 €625,500.00 €625,500.00 €625,500.00 €625,500.00
Total expenses €5,181,528.00 €5,181,528.00 €5,181,528.00 €5,181,528.00 €5,181,528.00
Net cash flow €7,893,217.69 €8,154,712.60 €8,421,437.41 €8,693,496.72 €8,970,997.22
Cumulative net cash flow €15,530,067.81 €16,047,930.29 €16,576,150.01 €17,114,934.14 €17,664,493.94
24. 10. Conclusion
The overall
11. Acknowledgments
We would like to thank Dr. Magdalena Hajdukiewicz for acquiring the 1 year worth of wind data
information from IRUSE.
12. References
1. Wind turbine spacing - http://en.wikipedia.org/wiki/Wind_turbine
2. Carbon Offset - http://www.iwea.com/iweafactsvideo - reference point 4) & 10)
3. Carbon Comparission - http://www.carbonfootprint.com/energyconsumption.html
4. Pollutant Emissions – Dr Rory Monaghan College of engineering and informatics -
https://nuigalway.blackboard.com
5. http://www.iruse.ie/
