Course of Power Production from Renewables Sources at Politecnico di Milano with Prof. P. Silva. In this work we analysed the investment feasibility of a wind plant on Garda Lake by checking performances and costs declared by the plant owner.

1. POWER PRODUCTION FROM RENEWABLES RESOURCES
Prof. Paolo Silva
Federico Bresciani 876795
Francesco Camberlingo 874429
Gianluca Frongillo 874548
Davide Massocchi 883781
Andrea Notaristefano 877887
2017-2018
Due diligence assessment of Rivoli
Veronese wind power plant

2. SUMMARY
1. Market analysis of Wind Energy ....................................................................................................... 1
1.1 Regulations and agreements .......................................................................................................... 1
1.2 Wind source in Italy......................................................................................................................... 1
1.3 Wind Energy in the World and in Italy ........................................................................................... 1
1.4 Annual capacity additions............................................................................................................... 2
1.5 Future projections of capacity growth........................................................................................... 3
1.6 Environmental impacts of Wind Energy......................................................................................... 4
2. Life cycle analysis............................................................................................................................... 5
3. Operational performance assessment ............................................................................................. 7
4. Commercial viability ........................................................................................................................10
4.1 Selection between the alternative solutions between 2 MW or 800 KW turbines...................12
5. Comparison with Monte delle Danzie power plant.......................................................................13
5.1 Business plan .................................................................................................................................14
6. Evaluation of the chosen turbine .......................................................................................................16
6.1 Rotor ..............................................................................................................................................16
6.2 Electrical System............................................................................................................................17
7. Sensitivity Analysis...............................................................................................................................18

3. 1
The aim of this report is to analyze the economic and technical feasibility of a wind farm on Monte
Mesa, Rivoli Veronese. This project started in 2008 and started to be built in 2012, being completed
in 2013.
1. Market analysis of Wind Energy
1.1 Regulations and agreements
The first important treaty was Kyoto’s protocol that has the objective to reduce the greenhouse gases
emissions, in particular CO2. During the period 2008-2010 Italy has to reduce CO2 emission 6.5% from
the 1990’s emission and sign the according at 12 November 2004.
After this treaty, the European Union introduced goals for the year 2020 in different sectors in
order to fix an objective after Kyoto. In the energy sector the 2020 goals were based on the three
pillars leading European energy policy: security of supply, competitive markets and sustainability.
1.2 Wind source in Italy
In our country the wind sources are mainly located in the central and southern regions and in the
islands. The Veneto’s region is poor from wind source as showed in the following wind Atlas
published by CESI. Monte Mesa has a particular orography: there is a channel between the
mountains from Trentino to Pianura Padana and Monte Mesa blocks partially this conduit, so the
breeze increases with an average velocity of about 5.5 m/s.
Figure 1: Average velocity at 75 meters in Italy and in Veneto
1.3 Wind Energy in the World and in Italy
Excluding hydro, wind power has an installed capacity, as renewable energy, that is the first in the
World, Europe and the second in Italy after only solar power.
Wind power contributed 5.4% of Italy electricity generation in 2015 (14.589 GWh). Italy is ranked as
the world's tenth producer of wind power.
The wind power industry has an experienced an average growth of 27% per year between 2000 and
2011.
Now 83 countries use wind power on a commercial basis and 52 countries increased their GW total
wind power capacity in 2010 (REN21, 2011). The new capacity added in 2011 totaled 41 GW, more
than any other renewable technology (GWEC, 2012). This means total wind power capacity at the
end of 2011 was 20% higher than the end of 2010 and reached 238 GW by the end of 2011.

4. 2
Figure 2: Cumulative capacity wind power in the world
The top ten countries by installed capacity accounted for 86% of total installed wind power capacity
worldwide at the end of 2011 (Figure 3).
Figure 3: The Top ten countries by installed wind capacity, end-2011
Now China has an installed capacity of 149 GW, 57 times the capacity they had in 2006. China now
accounts for 30% of global installed capacity, up from just 3% in 2006.
1.4 Annual capacity additions
The global wind power market was essentially flat in 2009 and 2010 during the financial crisis, but
in 2011 capacity added was 40.6 GW up from 38.8 in 2010. Onshore wind accounted for 97% of all
new capacity additions in 2010.
The market is still dominated by onshore wind and there remain significant onshore wind resources
yet to be exploited. However, the offshore wind market is growing rapidly. Worldwide, 1 162 MW
was added in the year 2010, with a total installed capacity of 3 118MW.
Europe installed 12.5 GW of gross additional wind capacity in 2016. This was 3% less than the new
installations in 2015. Now, with a total installed capacity of 153.7 GW, wind energy overtakes coal
as the second largest form of power generation capacity in Europe.

5. 3
1.5 Future projections of capacity growth
The wind industry has faced a difficult period. During the financial crisis the low order levels
translated into lower capacity additions in 2010 compared with 2009, in the key markets of Europe
and North America. However, global capacity still increased by one-quarter in 2010 and the outlook
for the coming years is cautiously optimistic. The world market of wind energy experienced solid
growth in the first half of 2011, recovering from a weak year in 2010.
The current analysis of the market suggests that as much as 85 GW of new capacity could come
online in the next two years based on the project pipeline for wind power projects already in the
process of being commissioned, constructed or which have secured financing.
The outlook for Europe: United Kingdom could become a significant player in the European market
in the coming years. The following picture of the Italy shows that only some provinces in the south
are saturated, in particular Foggia is the first province with a capacity of 21% of the country.
There are a lot of provinces in the north and in the central-north that are potentially climbers for
this technology.
Figure 4: Local distribution in Italy installed capacity in percentage in 2015
Asia, Europe and North America will continue to drive new capacity additions in the foreseeable
future. China continues to dominate new capacity additions, as ambitious plans and supportive
policies align. Although new capacity additions may not grow as rapidly as they have in recent years,
even so China has plans to reach 200 GW of installed capacity by 2020. India is likely to emerge as
an important new market, with capacity additions of 2 GW to 3 GW per year.
The outlook in North America is considerably more uncertain, due to legislative uncertainties and
the ongoing impact of weak economic fundamentals, but new capacity additions could increase to
12 GW in 2015. Since 2015 in Europe new capacity additions should increase to 14 GW and by the
end of that year total installed capacity to 146 GW.
In Latin America new capacity additions are projected to grow strongly from 0.7 GW in 2010 to 5
GW in 2015, increasing cumulative installed capacity from 2 GW to 19 GW. This rate of growth is
less than the excellent wind resource could support, but encouraging developments in Brazil,
Mexico and Chile are offset by a lack of political commitment and supportive policy frameworks
elsewhere.
The outlook for Africa and the Middle East is particularly uncertain, but new capacity additions
could increase ten-fold from 0.2 GW in 2010 to 2 GW in 2015. Africa has an excellent wind

6. 4
resource, although it is not evenly distributed and there is potential for Africa to see much stronger
growth rates in the future.
Figure 5: Projected growth in global wind power annual capacity additions and cumulative installed capacity, 2014 to 2019
1.6 Environmental impacts of Wind Energy
We now list the main disadvantages of this renewable energy technology:
• Visual impact: The most important environmental impact for the Monte Mesa’s project is
the skyline effect: the wind turbine considering the height of the tower and the rotor
diameter is totally 120 meters about half of the height of the hill. An option to avoid this
problem is to build a trellis for the tower.
• Noise: At distance of 300 meters the total noise is about 45 dB and at distance of 1,5 km the
noise is negligible.
• Birds/bats mortality: Wind turbines kill fewer birds than other types of human-caused direct
mortality, including: collisions with buildings (especially glass), vehicles, cats,
pesticides, hunting. Collision problem probably worse for bats than for birds, because many
bats appear attracted to moving rotor blades (for unknown reasons).
Parallelly, of course, there are environmental benefits:
• Pollutant emissions: there isn’t production of pollutants (SO2 and NOx) nor any kind of
hazardous waste.
• CO2 emissions: unless there are some emissions related to transport and construction of the
components and also foundation of a wind farm (26 g/kWh). There is an avoided CO2 per
MWh of:
44 ∗ 3600
17 ∗ 0.52 ∗ 47 ∗ 1000
= 381 tons/MWh

7. 5
considering an average efficiency of power plants in Italy equal to 52%, natural gas LHV of 47 MJ/kg
and natural gas MM of 17 kg/kmol. This avoided CO2 corresponds roughly to 8950 tons per year for
our 23.5 GWh/year.
2. Life cycle analysis
As seen, one of the main reasons for renewable energy is the reduction of CO2 and of
envinronmental impact in general. So, now we want to consider this impact due to all the
construction chain.
Figure 6: LCA of wind turbine
Wind turbines consist of many mechanical and electrical assemblies, which are comprised of many
sub-components. Therefore, it is a challenge for practitioners to gather the information from all
suppliers that provide the wind turbine components.
Information contained in the LCI is described below:
• Wind turbine characteristics: model is a 2.05 MW, three bladed, upwind pitch regulated
wind turbine with active yaw control (Senvion). The blades are 45.2 m in length with full
span control and a tower of 80 m in height. The rotor operates with a speed of 7.5-15 rpm.
• Wind turbine components: the rotor assembly is the key module of the wind turbine, and
comprised of the blades, hub, nose cone, and bearing. The rotor assembly is connected to
the nacelle assembly, which is attached at the top of the tower with a large, framed steel
structure. The nacelle assembly is comprised of a fibreglass housing that protects the
gearbox, generator, hydraulic system, main shaft, and yaw/pitch system from the weather.
The tower is made of large tubular steel sections that are painted, sealed, and bolted
together. The tower is attached to a reinforced concrete foundation with large threaded
rods, or is embedded into the concrete. As specific information was not available, the paint
and minor components such as bolts, fasteners, and internal wires were neglected.
• Transportation: transportation impacts result from emissions caused by the extraction and
production of fuel and its combustion during transport operations. Transportation of
materials, components, and assemblies to the turbine manufacturer has been neglected
due to the inability to trace the complete supply chain. The distance between the plant and
the industry is 1310 km.
• Wind turbine operation and maintenance: regular inspection visits with a diesel truck are
necessary on average three times a year. In addition, maintenance activities include
transportation and oil and lubricant changes, while rotor blade, gearbox, and generator
replacements are required once within a 20-year lifetime.

8. 6
Components Material Total mass (tons)
Rotor assembly Steel, Fiberglass, Epoxy and Cast
Iron
44.5
Tower Steel 200
Nacelle assembly
Steel, Copper, Fiberglass
reinforced plastic
71
Lubricant (20 years) 300
Foundation Steel 35
Concrete 775
Total mass 1400
• Dismantling and recycling: the end of life stage is an important aspect of the LCA. Steel,
copper, aluminium, and cast-iron recycling rates are at 90%, and non-recyclable waste is
transported to a landfill. Concrete is not recycled, so it is landfilled entirely (left in ground).
Foundations have a great impact on PM production: the lower the amount of concrete is
used, the lower the PM emissions are.
Material End of life treatment
Concrete Landfill 100%
Copper Recycling with loss 5%
Fiberglass Landfill 100%
Iron Recycling with loss 10%
Oil Incinerated 100%
Plastics Incinerated 100%
Rubber Incinerated 100%
Steel Recycling with loss 10%
The environmental impacts of the wind turbines are mainly due to the manufacturing stage, which
includes material extraction, manufacturing, and transport of components to the wind park. The
end of life stage produces negative environmental impact, reflecting a benefit to the environment
of recycling iron, steel, and copper. These results reiterate the importance on focusing on
sustainable design and sustainable manufacturing efforts early in the wind park development
process. Foundations have a great impact on PM production: the lower the amount of concrete is
used, the lower the PM emissions are.
The tower, rotor, and nacelle are found to have the greatest contribution to the environmental
impact in each case. For the tower, the large amount of steel required is the major contributor to
cradle-to-grave environmental impact. One of the outcomes from this LCA study is the confirmation
that the main life cycle environmental impacts of a wind turbine originate from the manufacturing
stage. Environmental impacts are driven by the material consumption, especially steel.
It was shown that the use stage has an almost negligible environmental impact due to maintenance
activities. In addition, it was found that recycling is important to the environmental profile of the
turbine, while transportation type can have a profound effect on life cycle impacts when
components must travel relatively longer distances.
The energy payback time is an important indicator for renewable resources. For this purpose, the
cumulative energy demand impact assessment method was used to calculate life cycle energy
requirement. Each of the two turbines has a size of 2.05 and would generate 3.5 GWh per year. For
such kind of turbine, literature suggests that the energy payback time would be around 0.8 years.

9. 7
3. Operational performance assessment
The turbine chosen for being installed in the wind farm of Rivoli Veronese is the Senvion MM92. All
the data used for the performance analysis of the turbine were taken directly from the Senvion
catalogue; here, a brief table containing the most significant parameters utilised in the study of the
machine operational performances is presented:
At first, we checked that the choice of the MM92 wind turbines was compatible with the selected
site for the wind farm installation, on Monte Mesa (Rivoli Veronese). We can observe that the
average wind speed at 80 m is between the turbine cut-in and rated velocities and therefore it is
possible to state that the selection of the wind turbine is correct. However, typically it would be
better to have an average speed of the wind closer to the design turbine speed, in order to avoid
excessive turbine off-time due to insufficient wind (lower than cut-in). In any case, the windiness of
the location (close to Garda Lake) is guaranteed mainly by two winds blowing on the Lake of Garda,
named Ora and Pelèr. These two famous winds, which blow regularly (although alternatively) during
the day and during the entire year, allow to make the turbines work without the risk of not having
enough wind. Indeed, as it will be shown, the wind farm equivalent hours are higher than the Italian
average for similar technology.
In order to assess the turbine performances and to estimate the expected annual energy
production, we made use of the wind speed data provided in the final report documentation of the
project. In particular, for each direction, the average wind speed was given and since the owner
didn’t published its anemometric campaign results, we adopted a statistical approach, analysing the
wind data by means of a Weibull distribution. In the report, apart from the average wind speed, the
Weibull parameters 𝜆 and k were given for each direction as well as the global values, which
summarise the wind distribution in the selected location. However, prior to using these values in
our calculations, it was necessary to check them: firstly, we computed the Weibull distribution
along each direction; secondly, we computed the global wind speed frequency distribution by
summing, for each speed, the corresponding speed frequency along all the different directions,
weighted by the overall frequency for which the wind blow towards that specific direction. At this
point, it was possible to evaluate the cumulative distribution function and then the complementary
cumulative distribution function:
Technical Data Rotor
Nominal Power 2.05 MW
Rotor diameter 92.5 m
Swept area 6,720 m2
Speed range 7.5 - 15.0 min-1
Max. tip speed 73 m/s
Rotor axis inclination 5°
Rotor cone angle 3.5°
Sense of rotation Clockwise (right)
Rotor position Up-wind
Cut-In wind speed 3.0 m/s
Rated wind speed 12.5 m/s
Cut-Out wind speed 24.0 m/s
Figure 7: Wind turbine power curve

10. 8
𝑓(𝑣; 𝑘, 𝜆) =
𝑘
𝜆
(
𝑣
𝜆
)
𝑘−1
𝑒
−(
𝑣
𝜆
)
𝑘
𝐹(𝑣; 𝑘, 𝜆) = ∫ 𝑓(𝑢)𝑑𝑢 = 1 − 𝑒
−(
𝑣
𝜆
)
𝑘
𝑄(𝑣; 𝑘, 𝜆) = 1 − 𝐹(𝑣; 𝑘, 𝜆) = 𝑒
−(
𝑣
𝜆
)
𝑘
By performing two times the natural logarithm of both equation sides, we obtained:
ln(− ln(𝑄(𝑣))) = 𝑘(ln(𝑣) − ln(𝜆)) → 𝑦 = 𝑘𝑥 + 𝐵
From this methodology we achieved:
𝑘 = 1.6265 (𝑣𝑠 𝑘 = 1.689) 𝑎𝑛𝑑 𝜆 = 6.3012 (𝑣𝑠 𝜆 = 6.2106)
After these evaluations, from which it was possible to assess the correctness of the values, we
decided to proceed the following calculations utilising the values calculated by the project
designers.
In this procedure, we also accounted for the fact that the data provided in the official project
documents were referred to a hub height of 40 m; therefore, we used the Hellmann correlation for
shifting them to a height of 80 m, that is the actual hub height of the selected turbines:
𝑣(𝑧) = 𝑣0 (
𝑧
𝑧0
)
𝛼
Within the Senvion catalogue, the machine power table, describing the power output from the
turbine for each wind speed, was supplied. Thus, by using these data together with the wind
statistical distribution, it was possible to estimate the annual electric energy production for a single
machine, assuming an availability factor of 82% to evaluate the available hours of the machines,
calculated with respect to the total annual number of hours, thus obtaining 0.82 x 8,760 h = 7,183.2
h (hours available for production, independently from the wind speed). The availability factor was
estimated considering both the turbine availability guaranteed by the manufacturer and the electric
grid one. With these hypothesis, the estimated electric energy produced by a single wind turbine is
Figure 8: Regression line that best fit the available data

11. 9
equal to 4700.28 MWh/y and then, since the project considers the installation of 5 MM92 turbines,
the global expected energy production stands at 23.49 GWh/y.
𝐸𝐸 [
𝐺𝑊ℎ
𝑦
] = ∑ 𝑃(𝑣𝑖)𝑓(𝑣𝑖)ℎ 𝑎𝑣
𝑖
The electric energy production estimated in the original project is of about 22.19 GWh/y and this
value is in accordance with what we obtained by analysing the wind turbines, referring to the
specific installation site orography. The difference in the value can be justified considering that the
evaluations made for the original project were performed at a height of 40 m, whilst it is more
correct to refer the calculations at the actual turbine hub height (80 m), where larger average wind
speeds are present (this is the reason why we obtained a higher production valuation).
Furthermore, in order to have an additional check on the expected production, we utilised a tool
made available by RSE (Ricerca sul Sistema Energetico). In particular, we had the possibility of
automatically calculating the annual productivity of the wind farm by selecting the geographic site
on a map, which contains the wind data measured in every region of Italy, together with the turbine
power parameters. At 80 m of height, an electric energy production of 23.1 GWh/y is calculated,
and this represents a supplemental check about the reliability of the results.
At this point, it was possible to calculate the wind farm equivalent (or full load) hours, that are
defined as the total annual hours during which the plant should work at its nominal power in order
to produce the given electric energy. This parameter is really useful to better understand if the
choice of the geographic site, with its specific wind characteristic, is reasonable and compatible
with the choice of the machines selected for the installation, from both an economic and a
technical point of view. The equivalent hours, calculated as the ratio between the EE and the plant
nominal power, are 2,292.07 h/y (2,164.88 h/y with EE = 22.19 GWh/y). In the Italian panorama,
the average equivalent hours for a large (>5MW) wind farm, is equal to 1,780 h/y in the year of
interest (2013). As it is possible to notice, the expected annual equivalent hours are above the
Italian average and, more in general, it is an absolutely valid value for the considered technology. If
we compute the capacity factor, defined as the ratio between the full load and the equivalent
hours, we get a value of 31.91%, which is an average result in the Italian panorama, where capacity
factors of wind farms stand at 20 ÷ 40%.
Figure 9: Wind speed statistical distribution

12. 10
4. Commercial viability
In a well-designed power plant, it is very important to understand if the fulfilment of the project is
commercially and economically feasible and in order to do that we analysed the business
framework by means of some useful indicators such as the NPV, LCOE and IRR. For the analysis, we
needed to assume the following data:
Discount rate 4,00%
Inflation rate 0,50%
Tax rate 38,00%
We also know that the lifetime of the plant has estimated to be of 20 years in addition to 1 year of
construction time and we considered the operating expenditure to be the 2% of the CAPEX, which
represent a reasonable assumption. In these costs we plan to include: all risk insurance,
maintenance, land royalty, assistance, vigilance, legal expenses and IMU tax on land properties.
Moreover, we calculated also the electric energy produced every year referring to a power plant
composed by 5 turbines even if the conclusive project provided for only 4 turbines.
Regarding amortization, we considered different annual rates as required by law: 9% for turbines
costs which would have led to 11.11 years to return the investment, while 4% for all the other
properties which account for only 30% of the CAPEX. For them, the return would have been after
25 years and so we decided to simplify the situation, assuming a mean value of 13 years for the
whole CAPEX. This means that fictionally we add two years of amortization per year due to turbines
and we renounce to 12 years of amortization on the rest.
Feed-in tariff 124 €/MW h
EETOT 23493,70 MW h/y
CAPEX 14.130.140,26 €
OPEX approx. 282602,8052
Amortization 13 years
A 1086933,866 €
Figure 10: Wind speed statistical distribution in the region of Rivoli Veronese

13. 11
The following table, given by the owner, sum up all the incurred and expected expenses:
A Interventi di progetto
A1&2 Interventi su viabilità 253.777,29
A3&4 Piazzole 195.146,97
A5 Fondazioni Aerogeneratori 660.341,21
A6 Ripristino Acquedotto 96.024,77
A7 Cavidotto elettrico 208.272,95
1.413.563,19
B Oneri per la sicurezza
B1 Indiretti 98.949,42
B2 Diretti 98.949,42
197.898,84
Importo lavori soggetti a ribasso (A-B2) 1.314.613,77
Importo complessivo dell’appalto (A+B1) 1.512.512,61
C Somme a disposizione dell’amministrazione
C1 Imprevisti 5% A+B1 75.625,63
C2 Lavori in economia 5% A+B1 75.625,63
C3 Fornitura Aerogeneratori 10.400.000,00
C4 Realizzazione connessione a sottostazione 500.000,00
C5 Servitù ed espropri 100.000,00
C6 Spese generali (IVA inclusa) 10.000,00
C7 Spese tecniche (IVA e CNPAIA incluse) 200.000,00
C8 IVA sui lavori e sulle forniture (10% A+B1+C1+C2+C3+C4) 1.256.376,39
12.617.627,65
Importo complessivo dell’opera (A+B1+C) 14.130.140,26
The evaluation took place in 2012 where the system of feed-in tariff auction was just implemented:
on the GME platform each producer offers a discount on the incentive, only knowing the starting
price (‘Tariffa incentivante base’) of 130 €/MWh and only a defined number of MW are accepted.
They knew that the tariff would have been high since there were not many participants, in fact it
happened that auction decreased the incentive only to 124 €/MWh.
Figure 11: Feed-in auctions in last years

14. 12
After the calculations, we got the following results:
YEAR Feed-in OPEX Revenue Profit Tax DCF Σ DCF PBT
-3 2009 - - - - - -11248,64 -11248,6
-2 2010 - - - - - -10816 -22064,6
-1 2011 - - - - - 0 -22064,6
0 2012 - - - - - -14130140,3 -1,4E+07 1
1 2013 124 282602,8 2913219 1543682,6 586599,4 1965401,037 -1,2E+07 2
2 2014 121,52 284015,8 2854955 1484005,2 563922 1855600,121 -1E+07 3
3 2015 119,0896 285435,9 2797856 1425486,02 541684,7 1751976,418 -8579227 4
4 2016 119,0896 286863,1 2797856 1424058,85 541142,4 1683836,335 -6895391 5
5 2017 119,0896 288297,4 2797856 1422624,53 540597,3 1618342,479 -5277049 6
6 2018 119,0896 289738,9 2797856 1421183,04 540049,6 1555392,216 -3721656 7
7 2019 119,0896 291187,6 2797856 1419734,35 539499,1 1494886,888 -2226769 8
8 2020 119,0896 292643,5 2797856 1418278,41 538945,8 1436731,658 -790038 9
9 2021 119,0896 294106,7 2797856 1416815,19 538389,8 1380835,365 590797,6 9
10 2022 119,0896 295577,3 2797856 1415344,66 537831 1327110,38 1917908
11 2023 119,0896 297055,1 2797856 1413866,77 537269,4 1275472,469 3193380
12 2024 119,0896 298540,4 2797856 1412381,5 536705 1225840,662 4419221
13 2025 119,0896 300033,1 2797856 1410888,8 536137,7 1178137,128 5597358
14 2026 119,0896 301533,3 2797856 2496322,5 948602,5 893769,7048 6491128
15 2027 119,0896 303041 2797856 2494814,83 948029,6 858874,9116 7350003
16 2028 119,0896 304556,2 2797856 2493299,62 947453,9 825339,6934 8175343
17 2029 119,0896 306078,9 2797856 2491776,84 946875,2 793111,171 8968454
18 2030 119,0896 307609,3 2797856 2490246,45 946293,7 762138,5188 9730592
19 2031 119,0896 309147,4 2797856 2488708,4 945709,2 732372,885 10462965
20 2032 119,0896 310693,1 2797856 2487162,67 945121,8 703767,3156 11166732 NPV
LCOE [€/MW h] 65,14451367
IRR 12,375%
The levelized cost of energy has been calculated considering the value of the feed-in tariff when the
NPV is equal to zero and represents the lifetime costs divided by the energy production.
The internal rate of return, instead, has been calculated considering the value of the discount rate
when the NPV is equal to zero and measures the profitability of potential investments. Generally
speaking, the higher a project's internal rate of return, the more desirable it is to undertake the
project.
Both the indicators, in addition to the NPV and the PBT, show us that the investment is very
profitable because we obtain a value of LCOE that is roughly 50% less than the feed-in tariff, which
means that we sell the energy we produce at a tariff that is the double of the actual one and a value
of IRR that is very far from the discount rate therefore we could support even higher discount rate
obtaining, anyway, a profit.
As far as the NPV is concerned, we see that at the end of the estimated lifetime we obtain a value
that is roughly the double of the total cost of our investment, which means that this power plant
has the potentiality to recover all the money necessary to build the plant, and to gain almost the
same amount of payed money.
4.1 Selection between the alternative solutions between 2 MW or 800 kW turbines
For this project, there were the possibility to install either 8 turbines of 850 kW or 5 of 2.05 MW.
The commission that had to find the best option decided to use the 5 wind turbines of 2.05 MW
this because: the impact on the landscape is less than creating a long series of 8 wind towers. A
view generally accepted by all the wind operators is that is better a lower number of wind turbines,

15. 13
but of higher power, to allow higher production of electrical energy from RE with lower
environmental impacts. This because of the dimensional ratios: the size of 2.05 MW and 850 kW
have a ratio between the height at the hub around 1.3 (80/60), between the diameter of the rotors
around 1.7 (90/53); this means a ratio of power of 2.5 and around 2.7 on production.
So, the benefits (production from RE) are more than the double (around 2.7) using the greater wind
turbines, while the visual impact, linked with dimension, is less than 1.5.
Moreover, the turbines of greater size have a lower rotational speed than a medium size turbine.
The next table takes into account all the effects on different aspects of the two configurations
available:
M.U. 5 turbines 8 turbines
Occupation of ground m2
2.290 1.230
Excavation Total m3
29.342 32.951
Material balance m3
+568 +2.791
Acoustic impact + -
Barrier effect + -
Skyline impact - +
Interference with landscape constraint n. 1 2
Interference with community habitats = =
Energy production MWh/year 23.49 13.792
CO2 avoided ton/year 8950 5550
So, despite the higher skyline effect, the 5 turbines are better than the 8 because of lower barrier
effect. One of the main benefits of the 2.05 MW turbines is the 38% less of CO2 emitted.
5. Comparison with Monte delle Danzie power plant
We decided to compare the plant with another on “Monti delle Danzie”, near Affi and so also to
Rivoli Veronese. This plant is owned always by AGSM and was built in 2016 so formally this is a
comparison a posteriori.
In this area the orography of the ground and the presence of winds, give to the area a suitable
anemometric condition to build a wind farm. The level is on average 250 meters over the sea level.
In the next picture there is the map of the area, where the positions of this project and the previous
one of Monte Mesa are indicated.
Figure 12: Map of the two plants under analysis
The first step was to study the area from a technical and environmental aspects. The strengths of
this site are:

16. 14
• There aren’t residential areas with high density of people in the neighboured;
• No prohibitive slopes on the hill;
• Good wind potential, as the other site under analysis;
Great efforts are done in order to allocate the wind turbine and the relative pitches minimizing the
civil work necessary and the visual impact.
Once the site is chosen, this has a great influence on the kind of wind turbine to use. The area has in
the neighboured the previous plant of “Monte delle Danzie”, so the new two turbines will form with
the previous once a continuous line directed on the east-west direction.
The same kind of turbines of the previous project is chosen because in this way a visual harmony is
created on the Moreniche hills: they have a nominal power of 2.05 MW with a height of 78-85
meters with a diameter of 80-90 meters.
5.1 Business plan
In the economic analysis performed on this plant we assume:
Total Nominal Power Installed 4.1 MW
Production estimated by designer 7 GWh/year
Equivalent Hours 1708 h
Feed-in Tariff 130 €/MWh
Discount rate 4 %
Inflation rate 0.5 %
Tax rate 38%
Year of construction 1 y
Anemometric campaign 2 y
The feed-in tariff is calculated based on the Italian regulation provided by GSE. Since the plant has a
power lower than 5 MW, it can access to the so called “Tariffa Incentivante Base” for the current
year that was 130 €/MWh. This incentive tells the price at which the producer can sell the energy to
the grid, while if he decides to self-consume the electricity, the incentive will be equal to 130
€/MWh minus the average price of electricity. This is not the case of the plant under investigation,
where all the electricity is sold. The subsidy can be exploited for 20 years from the request that is
more or less the duration life of a wind turbine.
The voice “Costs” can be explained as following: for the first two years it takes into account the
price of the anemometric campaign; at the year 0 is equal to the initial investment; for the others is
the O&M costs, computed taking into account maintenance cost and the other already mentioned
in the previous business plan, corrected with the inflation.
The calculations here after we consider the amortization:
For its computation, from 2017 in Italy is available the “Super Ammortamento”, a form of financial
help to encourage investments: for each year, the amortization can be evaluated considering the
9% of the 140% of the technological payment (wind turbine purchase). So, the taxes can be
discounted considering the 140% of the purchase prize. Dividing the initial technological investment
for the amount so found, the depreciation with this financial help can be applied for the first 11
“Superammortamento” 524160 €
Years of “superammortamento” 11.111 €
Depreciation civil work 12 years 158330.25 €
Depreciation first 11 year 682490.25 €
Depreciation 12 year 216570.25 €

17. 15
years, while in the 12 year the remaining is considered. For the civil opera and transportation, the
amortization is calculated considering 12 years of depreciation.
Year Revenues Costs Tax Profit CF DCF Sum
-2 0 10000 0 0 -10000 -10816 -10816
-1 0 10000 0 0 -10000 -10400 -21216
0 0 6059963 0 0 -6059963 -6059963 -6081179
1 910000 60600 63426 166910 785975 755745 -5325434
2 910000 60903 63311 166607 785787 726504 -4598930
3 910000 61207 63195 166303 785598 698394 -3900537
4 910000 61513 63079 165997 785408 671370 -3229167
5 910000 61821 62962 165689 785217 645391 -2583775
6 910000 62130 62844 165380 785026 620417 -1963358
7 910000 62440 62726 165069 784833 596409 -1366949
8 910000 62753 62608 164757 784640 573328 -793621
9 910000 63066 62488 164443 784445 551141 -242480
10 910000 63382 62369 164128 784250 529811 287331
11 910000 63699 62248 163811 784053 509306 796637
12 910000 64017 239177 629413 606806 379009 1175646
13 910000 64337 321352 845663 524311 314888 1490534
14 910000 64659 321230 845341 524111 302661 1793195
15 910000 64982 321107 845018 523911 290909 2084104
16 910000 65307 320983 844693 523710 279613 2363717
17 910000 65634 320859 844366 523507 268755 2632472
18 910000 65962 320734 844038 523304 258317 2890789
19 910000 66292 320609 843708 523099 248285 3139074
20 910000 66623 320483 843377 522894 238642 3377716
The result gives a PBT of 10 years, while a NPV of 3377716 €. These results are worse than the main
project under consideration because in Monte Affi the equivalent hours available for the power
production are lower, but the turbines were selected equal to the next once in order to ensure
harmony to the land scape, so there was not the possibility to select the more suitable for that site.
-20
-15
-10
-5
0
5
10
15
-3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
DCFM€
Year
Monte
Affi
Monte
Mesa
-2
-1,5
-1
-0,5
0
0,5
1
1,5
-3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
DCF/InstalledPower
M€/MW
Year
Monte Affi
Monte
Mesa
Figure 13: Economic comparison

18. 16
One advantage of Monte Affi plant is the higher feed-in tariff: this because it has a size lower than 5
MW and for these Italian legislation gives higher incentive. Another advantage of Monte Affi is the
possibility to access to the “Superammortamento”. Despite this, the higher cost of installation leads
to worst economic result of this plant.
In the chart above, we can see the trend of NPV along the lifetime of the plant: it is important to
underline that in the first years the slope of the curve is very high, but once the amortization period
ends the slope rapidly decreases due to the increase of the taxes.
Monte Mesa Monte Affi
PBT [years] 9 10
NPV [€] 11241000 3377716
Specific Investment [M€/MW] 1.38 1.48
NPV specific [M€/MW] 1.10 0.82
IRR [%] 12.38 9.61
Specific cost of investment in Monte Mesa is lower than Monte Affi because of a scale effect
despite the turbines selected are the same. In these computations is possible to calculate the scale
coefficient as:
𝐶
𝐶0
= (
𝑃
𝑃0
)
𝛼
So 𝛼=0.92, it’s a result in agreement with prediction, because generally wind turbines are not
affected by scale effect since the machine has each is own price and it doesn’t change if the scale
increases. In this case the margin between the two is due to lower impact of infrastructure costs in
the 10.25 MW plant than in the 4.1 MW.
6. Evaluation of the chosen turbine
In this paragraph, we will try to study the characteristics of the turbine installed in the plant to
understand the reasons of this choice and if it represents the best solution possible in the market.
It is worth noting that the turbine was chosen according to the terms of a public tender that
included also economic constraints other than technical ones. The considered turbine is the
Senvion MM92, a variable speed wind turbine with a rated power of 2,050 kW and a rotor diameter
of 92.5 m with electrical single-blade pitching system.
6.1 Rotor
The rotor consists of three rotor blades that are flange-mounted on the cast hub via a pivoted
double row four-point contact bearing. The rotor blades can thus be adjusted along their linear axis
via electrical pitch drives that rotate with the blades. The electrical blade pitch is used to limit the
rotational speed of the rotor and the power output. Furthermore, the pitch system is the main
brake of the WTG. In order to ensure the continued operation of the blade adjustment in the event
of a power failure or malfunction, each blade has its own, independent storage battery set that
rotates with the blade.
In the partial load range, when the WTG is operated below the rated power, the turbine works at a
constant blade pitch and variable speed to exploit the optimum rotor aerodynamics.
Within the nominal load area, when the WTG has reached its maximum rotor speed, it operates
with a constant nominal torque which is given by the generator. Changes of the wind speed are
controlled by the blade pitch.

19. 17
6.2 Electrical System
The blades are really long so they can’t rotate too fast to avoid high centrifugal stresses, but the
maximum speed supported is low for any generator even with variable speed. Hence, the system is
equipped with a gearbox, which multiplies angular speed by 120 for the outlet shaft. Then a
variable speed generator/converter system allows an operation of ± 40 % of the synchronous
speed. The variable speed operation offers, in connection with the electric pitch system, very good
results with regard to energy yield, efficiency, mechanical load, and quality of the power output.
The generator control enables an even power output with minimum fluctuation during partial load
operation. During nominal load operation the wind turbine power output is almost constant. The
principle of operation of this variable speed generator is based upon the concept of the
asynchronous double-fed induction generator with a converter using IGBT technology. The system
ensures the continuous power output by means of voltage and frequency values that have been
adapted to the grid independently from the rotor speed. Speed and power adjust automatically to
the prevalent wind conditions.
The presence of the brake system, consisting of a primary aerodynamic brake system and a
secondary mechanical brake system, permits to use both the pitch logic and the active stall logic in
order to keep the mechanical work constant and stay around the angle of stall of the turbine.
Moreover, the adoption of a double-fed induction generator ensures a high reliability and low O&M
costs renouncing at a higher efficiency obtainable by using a synchronous generator.
Figure 14: Power and performance curves
As we can see for the graph above, we notice that Cp varies significantly with wind speed. This goes
against our willingness to have the maximum power coefficient possible in the range between cut-
in speed and the rated speed by adapting the rotational speed of the turbine. Unfortunately, at
velocities really close to cut-in we can’t reduce ω as needed since it can change in a limited range
and so there will be bad performances in the initial region. Then we see a rapid growth and we get
an almost constant trend in the zone where we have the medium velocity in our site reaching the
maximum in proximity of the rated speed. After that, the velocity must be kept fixed in order to not
overstress the mechanical part of the turbine and avoid blades breaking, causing a cubic decrease
of the Cp which follows the inverse trend of the ideal power obtainable by our machine.
Accordingly, we can definitively assert that although the plant loses roughly the 20% of the
available wind due to the cut-in speed, the Senvion MM92 can exploit most of the energy available
in the considered site.
0
500
1000
1500
2000
2500
0 5 10 15 20 25
Wind velocity [m/s]
Power curve [kW]
0,00%
10,00%
20,00%
30,00%
40,00%
50,00%
60,00%
70,00%
0 5 10 15 20 25
Wind velocity [m/s]
Power coeff. Cp

20. 18
7. Sensitivity analysis
At the end of our study we look at the influence on plant feasibility of some parameters which
could change during the plant lifetime. This is done changing one variable by one and looking at
their effect on several parameters.
Firstly, we act on the discount rate to understand the variation of Levelized Cost of Electricity
(LCOE):
Figure 15: Levelized Cost Of Electricity at different discount rates
Obviously at increasing discount rate the profitability of the investment decreases, i.e. LCOE grows.
The impressive fact is that LCOE is strongly influenced since it almost doubles from the initial to the
final case. However, we should say that a variation like this of the discount rate is unlikely to
happen: we already assumed rDISCOUNT=4% as initial value and it’s already a remarkable number in
fact probably the real value will be lower. Moreover, we kept it constant along the whole lifetime
and, depending on the type of loan with the bank, we could have introduced an error but again the
eventual increase would not overcome 1-2%, causing a maximum variation on LCOE of 10 €/MWh.
We also performed a side analysis on the amortization years: obviously there’s a regulation which
fixes the amortization rate per year, but we want to understand what we would choose in case of
freedom.
Figure 16: NPV for different amortization years
We observe that Net Present Value is maximum if we choose an amortization time of six years: in
fact, too few years mean that we would pay all the taxes for a high subsequent period while too
40
50
60
70
80
90
100
110
0,0% 2,0% 4,0% 6,0% 8,0% 10,0%
Discount rate
LCOE [€/MWh]
0
5
10
15
0 5 10 15 20
Amortization years
NPV

21. 19
0
2
4
6
8
10
12
14
60 80 100 120 140
Feed-in tariff [€/MWh]
Net Present Value [M€]
0
5
10
15
20
25
60 80 100 120 140
Feed-in tariff [€/MWh
PayBack Time [years]
0%
5%
10%
15%
60 80 100 120 140
Feed-in tariff [€/MWh]
Internal Rate of Return
Figure 17: Influence of feed-in tariff on economic parameters
many years mean that we would limit taxes for a long period but the amortization per year would
be greatly lower since we would spread the investment over many years. Hence, if an eventual
future regulation would allow to decrease the amortization years (i.e. increasing the amortization
rate), we would suggest the plant owner to catch
that opportunity.
Another sensitivity we implement is a change in
the feed-in tariff, which is obviously one of the
main parameters affecting the plant revenues. We
choose to vary it from 66 €/MWh, which is the
incentive in 2016 auction, to 130 €/MWh which
instead is the starting price in all the auctions until
2016. It’s important to specify that once a plant
takes a tariff it keeps that incentive for 20 years.
Now we are discussing if this investment would be
convenient also in 2016 so formally this is an
evaluation made in 2015 by our consultant group.
The aim is to compare this investment with the
one in Monte Affi as if they were built in the same
year. In fact, we noticed that our plant is more
profitable than the other but in few years
incentives changed a lot and this could have
influenced the convenience. By the charts we
observe that NPV has a linear trend with the tariff
since in fact revenues are simply the product
between tariff and energy produced. Also the IRR
has a positive slope as higher revenues would
allow to accept an higher discount rate from the
bank. Finally, the Payback time is decreasing since
a higher tariff would compensate the sustained
costs in a lower time. Its value comes from an
interpolation between the subsequent years
where NPV changes sign, becoming positive.
Focusing on the first point of each chart, i.e. the
one corresponding to 66 €/MWh, we see very
poor performances: NPV is practically zero and PBT
is extremely close to 20 years, equal to the lifetime. Hence the investment would be strongly not
recommended in this case. So, Monte Affi would be better in this comparison since it would not be
affected by the reduced incentives having a power lower than 5 MW.
To be fair the reduced feed-in tariff for all the big plants (P>5 MW) would be a bit balanced by a
higher amortization per year (super/iper-amortization) which, as seen, can enhance the NPV. But in
general, the convenience to build new big wind farms from 2016 onwards has dramatically
decreased.
To conclude the report, we looked at the influence of wind average velocity.
In particular, we took the Weibull parameter λ [m/s], directly related to mean velocity, and we
reduced it from 0% to 20%:

22. 20
REDUCTION F (3 m/s)
EETOT
[GWh/year]
HEQ
[h/year]
NPV [M€] PBT [years]
0% 21,62% 23,49370381 2292,069 11,16673 8,549885
2% 22,28% 22,68837185 2213,5 10,35514 8,856869
4% 22,98% 21,87346747 2133,997 9,533907 9,235736
6% 23,70% 21,04997279 2053,656 8,704014 9,607105
8% 24,46% 20,21895799 1972,581 7,866543 10,04932
10% 25,26% 19,38158795 1890,887 7,022666 10,50133
12% 26,09% 18,539129 1808,696 6,173662 11,03162
14% 26,97% 17,69295562 1726,142 5,320914 11,58541
16% 27,90% 16,84455679 1643,371 4,465923 12,23613
18% 28,87% 15,99554155 1560,541 3,610311 12,91932
20% 29,90% 15,14764357 1477,819 2,755825 14,10096
We see that reducing the average velocity, the frequency distribution shifts to the left and the
cumulative frequency until 3 m/s increases: this means that we discard a greater amount of wind
because it is below the cut-in. Hence energy produced can only be lower, as depicted in the chart
below, and the same is for equivalent hours. Energy maxima shift to the left for more and more
severe reductions, following the frequency distribution. Moreover, what we lose under the cut-in is
obviously no more present at higher velocities, so we see lower and lower are below each curve.
Figure 18: Influence of wind reduction on EE
Consequently, also the economic parameters get worse. Nevertheless, a high reduction is not
realistic: even 5% of reduction would mean relevant errors in the wind estimation while our checks
returned us the goodness of the wind analysis. So, a yearly change of the wind is likely to happen
but without so high deviations and, above all, a change could also mean an increase of the wind for
some periods.
Hence, taking into account that wind estimations are checked and that the deviations will probably
compensate over years, but also considering that NPV is still positive, though low, even with great
wind reduction we have arguments to sustain the feasibility of this project and encourage the bank
to start up this investment.
0
20
40
60
80
0 5 10 15 20 25
Wind velocity [m/s]
Energy produced [MWh/year]
0%
10%
20%