SOLA5053 Wind Energy Converters

Wind Farm Project

Wind Farm Feasibility Studyby ”Vento”

Astrid Palm z3476879Ricardo Puerta de Gregorio z3476841

Usman Hassan z3424747Victor Chen z3329196Hanne Linde z3476949

May 25, 2014

Abstract

In this project a wind farm feasibility study with a production of 150MW was done upon a site located near Woomera in South Australia. Thewind resource was studied to find the average wind speed at hub heightusing the Weibull distribution of wind data measured. The proposal ofturbine selection and wind farm layout shows the design of the wind farm.The cost for the turbines, transportation of the turbines and payback timewas discussed giving a reasonable overview to the investors. Environmen-tal impacts shows that a wind farm would not give a large impact onlandscape and wildlife. Further a wind farm will have positive impactsregarding job opportunities for the local community.The result of this study was that the site chosen is fully viable to build aprofitable wind farm.

1

Contents

1 Introductionby Victor Chen 3

2 Sitingby everybody 4

3 The Wind Resourceby Ricardo Puerta de Gregorio 7

4 Wind Turbine Selection and Layoutby Astrid Palm 124.1 Turbine selection . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.2 Site design and optimization . . . . . . . . . . . . . . . . . . . . . 134.3 Losses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

5 Financial Analysisby Usman Hassan 165.1 Transportation Cost . . . . . . . . . . . . . . . . . . . . . . . . . 165.2 O&M Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165.3 Operational Revenue . . . . . . . . . . . . . . . . . . . . . . . . . 175.4 Subsidies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175.5 Decommission Costs . . . . . . . . . . . . . . . . . . . . . . . . . 185.6 Cost and payback . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

6 Environmental Impactsby Hanne Linde 18

7 Social Impactsby Victor Chen 207.1 Local impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217.2 Labour costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217.3 Electrical system and grid connections . . . . . . . . . . . . . . . 22

8 Conclusionby everybody 24

9 References 25

2

1 Introductionby Victor Chen

’Vento’ is a consultancy group that have done a feasibility study on buildinga wind farm near Woomera in South Australia. This report thoroughly coversthe literature review, concept design, social and environmental impact, economicand legal issues. Project ‘Vento’ will import wind turbines from a company inDenmark called Vestas Wind systems A/S. And the wind farm site is locatedat 3132’21.14”S 13648’44.85”E.The report is structured as following:•Wind resource is covered by Ricardo Puerta de Gregorio. In this part, he thor-oughly discuss the wind situation that our wind farm would experience.•Wind turbine selection and layout is covered by Astrid Palm. In this para-graph, she covers the technical reason for selecting the turbine from Vestas, andalso states the layout of the wind farm.•Financial analysis is covered by Usman Hassan. In his part, he covers the totalcost of the wind farm and discuss the payback period of the wind farm. He alsostates the reasons for the investors to invest in this project.•Environmental impact is covered by Hanne Linde. In this part, she states thepollution and environmental impact that might take place in this area, and dis-cuss objectively about building a wind farm for local residence.•Social impact is covered by Victor Chen. In this part he discuss local impactfrom a noise pollution point of view. Also he discuss about the salary and labourcost to build a wind farm.

3

2 Sitingby everybody

We have chosen to look at wind farm sites mainly in South Australia becauseof the strong winds that occur there. After some research we have decided togo with a site near Woomera.The pros for choosing this site are:• Transmission lines available (53.4 km away)• Desert area; no disturbance• Flat area• Infrastructure; roads already exists for transport• No other wind farms at this site• Acceptance from inhabitants is not considered as a problem since there al-ready are a lot of wind farms in South Australia• Easy access of wind dataThe cons for choosing this site are:• Some parts of Woomera are used by the Australian Governement as a testrange and is thereby restricted for public access• Potentially increase of maintenance costs due to sand and dust• The new Australian Government are planning to abolish the carbon tax whichcan decrease our profitability

The average speed of our weather station varies in a range from 4.7 m/s to5.3 m/s, depending on the number of samples that we are considering. It ispossible to see our weather station location in figure 1.

4

Figure 1: Location of weather stations in SA (BoM 2014).

With the objective of considering the wind direction of the site, it is necessaryto look at the wind direction measured from the weather station. This can berepresented by a wind rose as viewed in figure 2 and 3. It is made by analyzingthe wind direction for 1 year, at 2 different hours of the day, 9am and 3pm(BoM 2014):

5

Figure 2: Wind rose at 9am (BoM 2014).

Figure 3: Wind rose at 3pm (BoM 2014).

It is possible to say that the wind direction maintains constant during allday and year, predominantly blowing from the South, South East and SouthWest. This information helps when building the turbines in such a manner thatthey can use most of the wind during the day by facing them towards the wind.

6

Other sites that we considered was Port Augusta which had transmission linesand infrastructure but because of the low average wind speed and the lackof wind data we could not go for this site. The city of Carnarvon, locatedin Western Australia, had a huge wind speed always blowing from the South.However the area to build the wind farm was not big enough for our project.

3 The Wind Resourceby Ricardo Puerta de Gregorio

As our site is located near the small city of Woomera, the wind data used istaken from the Weather Station of Woomera, gathered from 1998 to 2011 bythe Bureau of Meteorology. The level of the anemometer is 10 meters so allthe wind velocities were taken at this height, and the roughness factor of thesurface is 0.3 metres (BoM 2014). The weather station is located at the airportof Woomera and by ’Google Earth’ the existence of small trees can be noticed,which could explain the higher value of the roughness as well as the influence ofthe airport. Firstly, the average wind speed at the weather station was foundby ’Excel’, using the following formula:

va =1

N

N∑i=1

vi = 4.86m/s (1)

where N = 115072 is the number of observations and vi is the wind speedat each observation. The standard deviation of the sample can be calculated aswell:

σv =1

N − 1

√√√√ N∑i=1

(vi − va)2 = 2.368 (2)

In order to correctly evaluate the wind speed distribution and fluctuationsduring the day, the Weibull distribution can be used. Then two parameters hasto be figured out, ’c’ and ’k’, which is the scaling and shape factor respectively.These are controlling how the function will spread out. The formulas to calculatethese parameters are (Kay 2014):

k =

(σvva

)−1.086

= 2.18 (3)

c10m = va(0.568 + (0.433/k))−1/k = 5.49m/s (4)

The roughness of semi desert areas and tall grass can be set to 0.1 m (Douglaset al 2009, p. 67, 117-128) and this will be assumed for our chosen wind farmsite. As the roughness is not the same for the wind farm site and the weatherstation, it is necessary to calculate the factor ’c’ at free stream height i.e. wherethere is no influence by the roughness:

7

cfs = c10mln(Hfs/z0)

ln(H/z0)= 10.82m/s (5)

The free stream height Hfs depends on the terrain and it will be consideredto be 300 m, which is the height of open grassland area (Kay, 2014). This cor-responds well with our flat weather station with small trees. z0 = 0.3m is theroughness factor and H = 10m is the height of anemometer.

Now it is necessary to calculate the factor ’c’ at hub height. The majorityof the wind turbines considered in our project have a hub height of HH = 94m,therefore the ’c’ factor was scaled to that height. With a roughness factor ofzH = 0.1m at the wind turbine site we get:

cH = cfsln(HH/zH)

ln(Hfs/zH)= 9.25m/s (6)

And then, the average wind speed at hub height can be figured outby rear-ranging (4):

va = cH(0.568 + 0.433/k)1/k = 8.18m/s (7)

One thing to notice is that the average wind speed at the site chosen is al-most twice as encountered at the weather station, 4.86 m/s and 8.18 m/s. Mostof the wind turbines work between 3 m/s and 25 m/s, therefore an average windspeed of 8.18 m/s indicates that this site has a good power potential. However,just knowing the average is not enough to determine whether a wind farm canbe projected or not. Other factors can be explored in order to define better thefrequency of the wind, which is really important. Sometimes the wind directionkeeps changing a lot during the day and this can have a negative influence onthe power generated by the wind farm.

The Weibull probability density function, PDF, can be used to get a morecomplex view of the wind data. The probability for a particularly windspeed vis:

p(v) =

(k

c

)(vc

)k−1

exp

(−(vc

)k)(8)

in ’Excel’ it is possible to find the values of the PDF when varying v, andplot the graphs related to the weather station and the site chosen, see figure 4:

8

Figure 4: PDF for the wind farm site and the weather station.

We can see that the frequency of lower wind speed is higher at the weatherstation compared to the wind farm site, the latter having more probability ofreaching huge values of wind velocities.

The Weibull cumulative probability, CDF, which is the integration of thePDF, will facilitate to come up with the percentages of being at certain windspeeds. This can be found by limiting an interval of the curve calculated by thefollowing formula:

p(v) = 1− exp

(−(vc

)k)(9)

9

Then a graph can be generated, see figure 5, to visualize the CDF whenvarying v:

Figure 5: CDF for the wind farm site and the weather station.

The graph shows exactly what is expected; the weather station, with lowerwind velocities, grows faster and reaches the cumulative probability of 1 first,thus the chances of finding huge wind speeds here is very low. On the opposite,the wind farm site takes longer to develop and reaches the value 1 later, culmi-nating in higher wind speeds encountered.

Further the CDF can be used to figure out the bins, which is the probabilityof being between a certain range of wind speeds. In ’Excel’, this can easily bedone with just calculating the difference of certain points of the curve. Finally,the number of hours the wind will be blowing at a certain range of speeds canbe found by multiplying the bins by the number of hours in one year, 8760.Below, figure 6 is showing this information:

10

Figure 6: Histogram showing the binned wind speeds per year.

It can be noticed that the majority of hours in one year, the wind will beblowing in a range from 3m/s to 25 m/s. This is within cut in and cut outspeed, which is really important to guarantee a stable power generation all thetime.

As mentioned in the siting section the constant wind velocities and directionimply that Woomera would be a good place to construct a wind farm. The nextstep to conclude our assumption would be to choose the wind turbine. The totalpower generated and energy can be calculated and use the Weibull probabilitiesto check the number of hours the wind will be blowing at certain speeds, makinga relation with the power curve of the wind turbine.

11

4 Wind Turbine Selection and Layoutby Astrid Palm

4.1 Turbine selection

With an average wind speed at hub height of 8.18 m/s, we are within the rangeof an IEC 61400-1 class III turbine. As a preliminary study, we have compared6 turbines from 4 suppliers, all of varying size, speed characteristics and poweroutput, see figure 7 for the results. All turbines are in class II/III.

Figure 7: Turbine characteristics (Vestas 2009 and WinWinD 2014).

We wish to compare the capacity factor for each turbine. This metric is abetter basis for comparison than the annual energy output as a continuous poweroutput is essential. The distributed power output is obtained by calculating theexpected amount of hours within each power range based on the power curve foreach turbine and the scaled Weibull distribution for wind speeds at hub height.

The power curves are obtained using a wind energy calculator (Suisse EoleGeschaftsstelle 2014). The power curves obtained in the calculator are basedon a standardized density of air. The actual density at hub height at our sightwill depend on the local Mean Sea Level Pressure and temperature and can becalculated based on the data obtained from the weather station. We choose touse the given power curves for each turbine as they primarily will be used tocompare our different options.

The expected power outtake for each power range can now be calculated,from which the annual energy output Ea, the Power output Pw, the averagePower output Pavg and the capacity factor Cp can be found by the followingrelations respectively (Nampalli 2013):

12

Ea =

N∑i=1

Pwi · vi ·∆t (10)

Pavg =

∑Pwi · ui

Hours/year(11)

Cp =Ea

Prated ·Hours/year(12)

Based on this analysis we see that, when only considering the capacity fac-tor, the Vestas V112/3000 (possibly the V112/3075) turbine is the best optionfor our site.

Further considerations will be done on the basis of the Vestas V112/3000turbine, with characteristics given in figure 8. This turbine is designed for lowand medium wind speeds and is applicable all over the world.

Figure 8: Our chosen turbine. Operating Hours are based on wind speeds overcut in speed and below cut out speed, i.e. the expected amount of hours that theturbine will deliver power, and do not account for down time due to maintenanceor damages.

The Betz limit (wake neglected and steady state flow) yields an upper limitfor the capacity factor. Our capacity factor of 0.4998 lies fairly close to thislimit. As no wake losses or mechanical losses are accounted for, the actual ca-pacity factor will be significantly lower.

4.2 Site design and optimization

After having selected a turbine, one can start looking at the site layout, the goalbeing to maximize the power outtake.

13

Firstly we wish to make maximum use of the available land. Obviously, themore turbines we add, the higher the potential power outtake will be and thehigher the potential income. However this goal has to compromise with the wishto maximize the turbine capacity factor as the spacing of the turbines affectsthe wake losses. Also, when you place several turbines behind one another, thedown stream turbines are more prone to fatigue due to the induced turbulences.Studies show that separating the turbines by 8-10 rotor diameters in the down-stream direction and 5 rotor diameters in the crosswind direction leads to verylow wake losses, as the turbulences are reduced to about 10% (Bright Hub Inc.2012). This coincides well with the suggested spacing of 7-10 rotor diameters inthe strongly predominant wind direction from the tutorial notes (Kay 2014).

We are aiming for a total installed capacity of about 150 MW. Due to down-stream wake losses we wish to minimize the number of rows normal to thepredominant wind direction. With turbines of a rated capacity of 3 MW, aspacing of 10 rotor diameters in the downstream direction and 5 diameters inthe cross-stream direction, we suggest the following layout for the wind farm:

Figure 9: The layout of our windfarm.

5 rows in the prominent wind direction with 10 columns in each give us atotal of 50 turbines and a total installed capacity of 150MW.

14

4.3 Losses

The induced velocities and turbulences downstream and cross-stream of eachturbine affect the power output of the other turbines. The downstream arraylosses are much larger than cross-stream so we mainly concentrate on the spac-ing of the turbines in this direction.

Using Katic’s empirical model for array losses (Kay 2014) we can determinethe losses between each row of turbines:

1− uxu0

=(1−

√1− cT )

(1 + 2kXD )2

, (13)

where ux is the wind velocity at a distance x, u0 is incoming velocity, cTis the thrust coefficient, k is the wake decay constant and X/D is the spacingratio of the turbines. Similarly, the relation between the scaling parameters inthe respective Weibull distributions is:

1− cxc0

=(1−

√1− cT )

(1 + 2kXD )2

(14)

Assuming a spacing of 10 rotor diameters in the downstream direction, thechange in Weibull parameter ’c’ and the corresponding losses for each row ofturbines are given in figure 10. We see that the wake losses increase for eachrow, leaving the rear turbines with a fairly low average power output. Since wein our site layout only have 5 rows in the downstream direction, the maximumarray loss will be of approximately 15% (between row 4 and 5).

Figure 10: Average power, total power per row and wake loss due to the differ-ence in ’c’.

Also, there will be annual losses due to both regular maintenance and repairof unexpected damages. As the records of failures and the corresponding down-time for different turbines is not public, the estimation of losses due to technical

15

failure involves several error sources and imprecise assumptions (Walford 2006).

According to data obtained by the National Renewable Energy Laboratory(NREL 2013), there is no significant difference in availability between turbinesof different power class or from different manufacturers. Most of them lie over90% and the average amount of downtime per year is 170 hours. Since our site islocated in a sandy area, a fairly higher assumption for expected downtime shouldbe done. On this basis we assume 190 downtime hours per year per turbine thefirst 15 operating years. Subtracting this from the already estimated operatinghours we get 7865 operating hours per year. The power and energy output foreach row is given in figure 11.

Figure 11: Average power and annual energy output for each row.

When array losses and downtime due to wind speeds outside the operat-ing wind speed range are accounted for, we have an annual energy output of464,908MWh.

5 Financial Analysisby Usman Hassan

5.1 Transportation Cost

The weight of each turbine and with blades and tower comes out to be 90tonnes. We are going to install 50 wind turbines thus the total weight comesout to be 4500 tonnes. The average cost of shipping is 0.07/tonne/km (Bureauof Transportation Statistics 2014). Considering our turbines are coming fromDenmark Aarhus to Adeliede we, find out the distance to be travelled is 20,800km (Searates 2014), calculating we get:

4500 · 0.07 · 20800 = $6, 552, 000 (15)

5.2 O&M Costs

Our O&M costs include insurance, maintenance , repair, spare parts and ad-ministration, this cost is about 1.7 (Morthorst, P. 2014) cents/kWh for a midsized turbine. (700-1500kW). Assuming the O&M costs decrease by the use oflarger sized Wind turbine our cost would come to be around 1.5 cents/kWh.

16

We are hoping to produce about 464,900,000 kWh , thus total O&M comes outto be $ 650,871,011

5.3 Operational Revenue

The amount of electricity produced by our wind farm in a year comes out tobe 464,907,865.6 kWh, the average spot price of wholesale electricity duringthe year 2010-2014 was $ 48.82 /MWh. The line losses and transformer losseswould amount to about 2% which would give us a total revenue through sale ofelectricity comes out to be $ 22.23 million.

5.4 Subsidies

Large-scale generation certificates can be obtained for wind farms, these arecalculated by the following formula (Clean Energy Regulator 2014):

TLEG–(FSL+AUX + (DLEG · (1–MLF ))) (16)

where TLEG is the total amount of electricity (in MWh) generated by theRET power station in the year, as measured at all generator terminals of thepower station in the year. 464,907.865 MWh for our plant.FSL is the RET power stations may be using a combination of fossil fuels andrenewable energy sources. Does not apply to our plant.AUX is the auxiliary losses relate to electricity used in the generation of elec-tricity and electricity used in the operation and maintenance of the RET powerstation. The auxiliary loss is not eligible for LGCs. However, electricity con-sumed in a manufacturing or production process can be eligible for LGCs. Thisdata is not provided by most large wind turbines company , thus it is very dif-ficult to ascertain. In Colder climates it is estimated to go up to 20% but forour site we take it 0%.DLEG is the net eligible generation which is exported to a distribution network,transmission network or a point of use. We are accounting for transformer losseswhen connecting to the grid which can be about 1%(Hulshorst 2009).MLF it the transmission losses are too be calculated through applying themarginal loss factor (MLF) to the amount of exported electricity. The MLFis calculated for each RET power station by the Australian Energy Market Op-erator (AEMO) in the National Electricity Market (NEM) regions. RET powerstations in non-NEM regions should contact their State or Territory governmentfor this information, where available - for example, the Independent Market Op-erator (IMO) in Western Australia. According to AEMO our plant is situatedwhere MLF turns out to be 0.9845Using the formula we get 457773 LGC’s. The price of weighted LGC for 2013was $ 25 (Green Energy Trading 2014) , thus our total revenue for LGC comesout to be $ 11,444,325

17

5.5 Decommission Costs

The cost of decommissioning the wind turbines is offset by the salvage value ofthe towers and turbine components to some part.

To decommission we have to remove the towers, remove concrete used infoundation and seed and re-vegetation for the land. If the land is to be usedagain for newer wind turbines this cost can be ignored.

Selling the scrap can be of significant value which includes,salvage value ofturbine , scrap value of tower steel, scrap value of generator components .

Estimated cost of decommissioning minus salvage value comes out to beabout $ 15,000.

5.6 Cost and payback

The capital cost for single wind turbine with installation comes out to be $ 3.75million.Using the costs above the simple payback comes out to be 6.3 years.

6 Environmental Impactsby Hanne Linde

When the turbines are in place there are several issues regarding their presencein the landscape. This can cause conflict with the people living there as wellas wildlife and surrounding flora. For people it is the visual and noise of theturbines and for wildlife such as birds a wind turbine can be fatal if they flyinto them (WEDPEIS 2014). These are subjects that needs to be carefullyconsidered before actually building a wind farm. The “aesthetic pollution” awind farm can bring to a landscape is for many people a big problem. A windfarm is big and the towers can be over a 100 meters tall. They are very visiblein the landscape due to their location in windy sites such as on top of hills ornear the coast (WEDPEIS 2014). People are different and so are their viewson what is beautiful and what is not. It is impossible to make a wind turbinethat everybody will be satisfied with, but we believe that our desert locationwill not get many protests since the population in the surroundings is low. Wealso believe that getting a general acceptance from the people living in SouthAustralia to be a non-problem because of the many wind farms already existingthere.

When wind turbines operates the rotating blades makes noise. This noise isfortunately not that prominent since the wind turbines only operate when thewind is blowing. Again, since our wind farm will be in a desert area, not manypeople is around to be annoyed by the noise.

The biggest problem with wind turbines is the impact that it can have onbirds and other flying wildlife such as bats. The findings of dead birds and bats

18

around wind farms in South Australia concludes that wind turbines are a threatto the flying wildlife (Sharp 2010). The deaths of some species can have impactsfurther down the ecological chain. For example if the population of raptors isdecreased, the population of rabbits and small mammals which is the raptorsfood, can increase, leading to pest (Sharp 2010). To minimize this threat a lotof things can be done. One thing is to build towers with smooth surfaces so itis impossible for birds to lay nest there. Another possibility is to do researchon the different bird and bat types living in the area and have turbines with aheight that does not match with the birds flying height. And also not placingthe wind farm in sites where birds usually fly over i.e. their migration route.There is a so called “important bird area” identified nearby Woomera and ourwind farm site (Birdlife 2012), around the Lake Torrens. This is an area wherethe birds are very sensitive to disturbance to their habitat. Our wind farm willbe at least 110 kilometers away from this lake so we believe that it should nothave a large impact on the bird life there. One creative way to stop or at leastminimize the rate of birds and bats flying into turbines is to paint the tower androtor blades in bright colors which can scare them away. Colorful turbines willof course be even more visible in the landscape which can be negative for somepeople as discussed above, but on the other hand this could be the beginningof a tourist attraction, creating more interest and enthusiasm of wind turbinesto the public. See figure 12 for an example illustration. To finance the costof building the wind farm, one or more of the turbines can be built with anobservation deck. This can attract tourists and create even more interest aboutwind turbines.

Figure 12: Illustration for a wind farm with colorful rotor blades (Singh 2010).

19

Our wind farm will be located near the highway A87 and because of theflat desert area no big impacts on the environment needs to be done by makingnew roads for transportation of the wind turbine components. Only some smallroads that goes to each turbine when setting up the wind farm and also formaintenance later. Trees, bush and flowers will therefore not be affected in alarge scale. From a map of soil types of South Australia (Atlas 2012), Woomerahas a mix of calcareous earth and crusty red soil. We believe that this willnot have a negative effect when building the foundation for the turbines. Theonly complication when building in a desert area is the extra maintenance ofthe rotor blades because of the dust and sand that can stick to the blades andecrease the efficiency.

The site where our wind farm will be set up is government land, but thereis one area in Woomera which is owned by the Australian Defense Force andhas strict entering regulations. It is the biggest military test range on land(Department of Defense 2014) and it is called Woomera Prohibited Area. Webelieve that some of the power from our electricity production can go to thismilitary base. That is also the reason why we chose to build a big wind farmwith a yearly production of 150MW.

In South Australia the consumption of 1 kWh gives 0.79 kg of CO2 (De-partment of Climate Change 2012). That means if this wind farm is to be builtthen SA would save 118,500 kg of CO2 compared to the electricity coming froma power plant.

7 Social Impactsby Victor Chen

Figure 13 shows the investment amount by states in Australia since year 2000.South Australia attracts the most investors throughout Australia in Wind En-ergy industry. In this report, it can be observed that there is more than 3000jobs created in 2012 for wind energy for all 5 states in Australia, and around750 direct jobs created. This indicates that South Australia cares about windenergy, and also shows a great advantage throughout Australia.

The South Australian government help investors to discover opportunitiesthere (Department of Manufacturing, Innovation, Trade, Resources and Energy2014). The government works with investment banks and encourage variousof investment methods, and also provide excellent service for international in-vestors. The wind turbines that we are choosing provide a 24/7/365 surveillance.Service include detecting potential errors and disruptions, as well as the main-tenance for the turbine.

20

Figure 13: Table showing investment by state since year 2000.

7.1 Local impact

The site that we are choosing is close to a small town and feedback from localcitizen would be essential for renewable energy projects. It is believed that asmuch as 80% of farmers and land owners would get important income frombuilding a wind farm (Clean Energy Counsil 2012). Also, a small majority,57%, of residents thought it is likely having a wind farm in the local area toprovide the growing of local business. Another important point that should beconsidered for the local residents is the noise problem from the wind turbinesmight influence their lives. Noise levels should not exceed 35 dB at the receiverswith rural living, and 40 dB at receivers in other zone (Environment ProtectionAutorithy 2009). The wind turbine that we are choosing gives a 100 dB-106.5dB sound level range. The distance from the site that we are choosing andto the closest residence at the small city of Pimba would be about 120 kmestimated from ’google maps’. Therefore the sound that it generate would notbe a problem for residents living there, since sound level decreases 6 dB per unitlength (Sengpiel 2014).

7.2 Labour costs

Concerning the salary it is the wind technician that has the most important rolewhile building and operating a wind farm (Hubpages 2014). The salary wouldnormally be offered $45,000-$48,000 annually. To become a wind technician, oneshould complete a wind energy training program specific for wind technicians.And this would offer a high standard of work quality, and provide a stable windfarm operating period. For wind site labor, the normally payment is $22-$25per hour. This gives a clear financial plan for labor cost beforehand.Turbines would be constructed by ’Vestas’, the provider of the chosen wind

21

turbine. Even with the 54.6 meter blades there are no special fees. (Vestas2009)

7.3 Electrical system and grid connections

The electrical parts inside the turbine containing the inverter and the connec-tion grid is great for the wind situation in the chosen wind farm. There is onlytwo parts that requires attention in the electrical system we have on the windsite, which are the control and supervision and transmission efficiency.

Connection is necessary for wind site, therefore, strong powerful and efficientcables are located to connect all the wind turbine. The closest substation islocated at 3114’04.0”S 13649’53.0”E.

22

According to Google maps, the closest substation would be 53.4 km awayfrom the wind site. It is relatively far from the wind site, but on the other handit would be convenient to install due to the location of the substation near thehighway A87. See figure 14.

Figure 14: The nearest sub station, red marker.

After comparing with several dealers, a cable company in China calledSREXACT would provide a low price cable. Which is around $1 per meter.For a 53.4 km connection, it would cost around $110,000.

23

8 Conclusionby everybody

Overall, the wind resource was discussed for this wind farm, having a dominatewind direction from the South and an average wind speed of 8.18 m/s at hubheight. The wind turbine chosen has a cut in speed of 3 m/s and a cut out speedof 25 m/s which will generate energy rated power at 3kW. Doing the financialanalysis, it can be stated that the initial cost and the possible payback time of6.3 years are suitable according to the interests of our investors. Finally, theimpact on environment and social was thoroughly discussed, neither having anynegative impacts considering the local residents, live stock and wild animals.To conclude, it is possible to say that the wind farm feasibility discussed in thisreport would be viable and perfectly designed.

24

9 References

1. Front page picture: Red Nomad OZ 2012, ’Wattle Point Wind farm’,Available at: http://rednomadoz.blogspot.com.au/2012 12 01 archive.html#.U3WLfCgWfIU[May 15 2014]

2. Purple wind turbines: Singh, T. 2010, ’Painting Wind Turbines Pur-ple Will Save Wildlife’, Available at: http://assets.inhabitat.com/wp-content/blogs.dir/1/files/2010/11/purpleturbines-ed01.jpg [May 21 2014]

3. Atlas, Government of South Australia, 2012, ’Soil map of South Australia’,Available at: http://www.atlas.sa.gov.au/images/2Env Res4Soils.jpg [May15 2014]

4. Birdlife Australia 2012, ’Important Bird Areas’,Available at: http://www.birdlife.org.au/projects/important-bird-areas/iba-maps [May 15 2014]

5. Bright Hub Inc. 2012, ’Wind Turbine Minimum Spacing’, Available at:http://www.brighthub.com/environment/renewable-energy/articles/97151.aspx[May 15 2014]

6. Bureau of Transportation Statistics 2014, United States of Department ofTransportation,Available at: http://www.rita.dot.gov/bts/publications/commodity flow survey/2002/united states/pdf/entire.pdf[May 22 2014]

7. Clean Energy Council 2012, Wind energy community reasearch in Victo-ria, New South Wales and South Australia

8. Clean Energy Regulator 2014, Australian Government, ’LGC Eligibil-ity Formula’, Available at: http://ret.cleanenergyregulator.gov.au/For-Industry/Renewable-Energy-Power-Stations/LGC-Eligibility-Formula/lgc-eligibility-formula [May 22 2014]

9. Department of Climate Change 2012, Australian Government 2012, ’Aus-tralian National Greenhouse Account’,Available at: http://www.climatechange.gov.au/sites/climatechange/files/documents/03 2013/nga-factors.pdf [May 25 2014]

10. Department of Defence, Government of South Australia 2014, ’WoomeraProhibited Area’, Available at: http://www.defence.gov.au/woomera/about.htm[May 15 2014]

11. Department of Manufacturing, Innovation, Trade, Resources and Energy2014, Invest in South Australia, Government of South Australia, Avail-able at: http://www.southaustralia.biz/invest in south australia [May 152014]

25

12. Douglas, E.M., Beltran-Przekurat, A., Niyogi, D., Pielke, R.A., and Vorosmarty,C.J. 2009, ’The impact of agricultural intensification and irrigation onland-atmosphere interactions and Indian monsoon precipitation – A mesoscalemodeling perspective’, Global and planetary Change

13. Environment Protection Authority South Australia 2009, ’Wind farmsenvironmental noise guidelines’

14. Morthorst, P. 2014, ’Costs and Prices’,Available at: http://www.ewea.org/fileadmin/ewea documents/documents/publications/WETF/Facts Volume 2.pdf [May 22 2014]

15. Green Energy Trading 2014, Available at: http://greenenergytrading.com.au/[May 22 2014]

16. Hubpages 2014, ’Wind Technician Salary’, Available at: http://windenergy.hubpages.com/hub/wind-technician-salary [May 15 2014]

17. Hulshorst, W. 2009, ’Estimation of the energy losses of transformers atwind turbines’, Available at: http://www.leonardo-energy.org/estimation-energy-losses-transformers-wind-turbines [May 22 2014]

18. Kay, M. 2014, SOLA5053 Wind Energy Converters, lecture notes, Univer-sity of New South Wales

19. Nampalli, N. 2013, SOLA5053 Wind Energy Converters, tutorial notes,’Tutorial 3 – Wind turbine Components, Concepts and Technology Selec-tion’, University of New South Wales

20. NREL 2013, ’Report on Wind Turbine Subsystem Reliability A Survey ofVarious Databases’, Available at: http://www.nrel.gov/docs/fy13osti/59111.pdf[May 20 2014]

21. Searates 2014, ’Distance and Time on your Website’,Available at: https://www.facebook.com/l.php?u=http%3A%2F%2Fwww.ewea.org%2Ffileadmin%2Fewea documents%2Fdocuments%2Fpublications%2FWETF%2FFacts Volume 2.pdfh=EAQFaAhZ [May 20 2014]

22. Sengpiel, E. 2014, ’Damping of Sound Levels vs. Distance’, Available at:http://sengpielaudio.com/calculator-distance.htm [May 22 2014]

23. Sharp, Andy, (Lower North Natural Resource Management Group, Gov-ernment of South Australia) 2010, ’Briefing note on the effects of windfarms on bird and bat populations’,Available at: http://www.nynrm.sa.gov.au/Portals/7/pdf/DENR/Briefing%20Note%20-%20Effects%20of%20Wind%20Farms.pdf [May 15 2014]

24. Suisse Eole Geschaftsstelle 2014, ’Windenergie-Daten der Schweiz’,Available at: http://wind-data.ch/tools/powercalc.php?type=ak&a=9.25&k=2.18&v=7.23&d=1.225&turbine=33&p%5B0%5D=0&p%5B1%5D=0&p%5B2%5D=47&p%5B3%5D=

26

149&p%5B4%5D=320&p%5B5%5D=573&p%5B6%5D=927&p%5B7%5D=1395&p%5B8%5D=1977&p%5B9%5D=2584&p%5B10%5D=2947&p%5B11%5D=2998&p%5B12%5D=3000&p%5B13%5D=3000&p%5B14%5D=3000&p%5B15%5D=3000&p%5B16%5D=3000&p%5B17%5D=3000&p%5B18%5D=3000&p%5B19%5D=3000&p%5B20%5D=3000&p%5B21%5D=3000&p%5B22%5D=3000&p%5B23%5D=3000&p%5B24%5D=3000&p%5B25%5D=0&p%5B26%5D=0&p%5B27%5D=0&p%5B28%5D=0&p%5B29%5D=0&abfrage=+Calculate+earnings+ [May 2 2014]

25. Vestas 2009, ’V90-3.0MW’,Available at: http://www.vestas.com/Files/Filer/EN/Brochures/Vestas V 90-3MW-11-2009-EN.pdf [April 7 2014]

26. Vestas 2009, ’V112-3.0MW’,Available at: http://www.vestas.com/Files/Filer/EN/Brochures/Vestas V 112 web 100309.pdf[April 4 2014]

27. Walford A. 2006, ’Wind Turbine Reliability: Understanding and Minimiz-ing Wind Turbine Operation and Maintenance Costs’,Available at: http://prod.sandia.gov/techlib/access-control.cgi/2006/061100.pdf[May 20 2014]

28. Wind Energy Development Programmatic EIS (WEDPEIS) 2014, ’Windenergy development environmental concerns’,Available at: http://www.windeis.anl.gov/guide/concern/index.cfm [May15 2014]

29. WinwinD 2014, ’Home – WinWinD’, Available at: http://www.winwind.com/WWD3.aspxdetailed-data [April 2 2014]

27