Economic analysis of wind projects

APPLICATION NOTE
ECONOMIC ANALYSIS OF WIND PROJECTS
Eclareon
April 2017
ECI Publication No Cu0191
Available from www.leonardo-energy.org

Publication No Cu0191
Issue Date: April 2017
Page i
Document Issue Control Sheet
Document Title: Application Note – Economic Analysis of Wind Projects
Publication No: Cu0191
Issue: 02
Release: Public
Content provider(s) Eclareon
Author(s): Eclareon
Editorial and language review Bruno De Wachter (editorial), Noel Montrucchio (English language)
Content review: DNVGL
Document History
Issue Date Purpose
1 October
2013
First publication in the framework of the Good Practice Guide
2 April 2017 Revised publication after review
3
Disclaimer
While this publication has been prepared with care, European Copper Institute and other contributors provide
no warranty with regards to the content and shall not be liable for any direct, incidental or consequential
damages that may result from the use of the information or the data contained.
Copyright© European Copper Institute.
Reproduction is authorized providing the material is unabridged and the source is acknowledged.

Page ii
CONTENTS
Summary ........................................................................................................................................................ 1
Introduction.................................................................................................................................................... 3
Lifecycle Cost Components and Benchmarks for a WPP.................................................................................. 7
Lifecycle of a WPP...................................................................................................................................................7
Total Costs of a WPP...............................................................................................................................................8
Economic Analysis ........................................................................................................................................ 13
Internal Rate of Return.........................................................................................................................................15
Net Present Value.................................................................................................................................................16
Payback Period .....................................................................................................................................................17
Levelized Cost Of Energy ......................................................................................................................................18
Risk Assessment ........................................................................................................................................... 21
Financing Alternatives .................................................................................................................................. 23
Conclusion .................................................................................................................................................... 25
Annex: Acronyms.......................................................................................................................................... 26

Page 1
SUMMARY
This Application Note presents and illustrates key elements associated with the economic analysis of wind
energy projects and is aimed at municipalities, cooperatives, investors, and companies that want to install
wind parks on their premises.
Over the past decade, wind energy capacity has increased significantly, mainly driven by national support
schemes. This enabled technological improvements and cost reductions per unit of installed power. More
recently, with the global financial crisis (and the associated tight financing conditions) behind us, appetite for
wind investments has increased. According to WindEurope, wind energy investments in Europe increased by
5% in 2016 with respect to 2015 (totaling €27.5bn of new investments in 2016). Wind energy investments
1
accounted for nearly 90% of the new renewable energy finance in 2016, compared to approximately 70% in
2015.
Wind investments can provide an attractive risk/return profile, as well as other potential benefits such as risk
diversification and a hedge against rising fuel prices. Currently, revenues from wind projects are usually based
on PPA revenues plus subsidies, which tend to be market-based (e.g. a premium over a market price).
However, the characteristics of recent wind energy auctions and Power Purchase Agreements (PPA) being
closed worldwide show that in some cases wind is already cost-competitive with traditional energy sources.
It is estimated that wind generation costs will decrease by approximately 10%
2
by 2020 as a result of expected
future improvements in key variables (i.e. CAPEX, capacity factor, financing, and OPEX),
 For onshore wind parks, higher capacity factors and CAPEX improvement are expected to drive
generation cost reductions.
 For offshore wind, financing cost and CAPEX reduction (through increased turbine capacity ratings
and hub height) will likely lead to generation cost reductions.
The viability of wind projects will depend upon a business model based on a stable scheme that enables long-
term predictable revenue streams, regardless of whether it is market driven (PPA) or politically driven (FiT).
Financing costs are highly dependent upon the stability of the regulatory framework (the more stable, the
lower the financing costs) and the risk profile of the investment (financing cost decreases with increasing
accuracy in estimates, better risk management, more industry experience, and more standardization).
In all cases, an economic analysis of the investment opportunity is required before undertaking the project.
Several financial indicators are useful for assessing the viability of the project, including IRR, NPV, and payback
period, among others. Moreover, it is advised that conservative assumptions be used in the financial model
and sensitivity analysis be performed to consider the impact of different scenarios on profitability.
Even though a wind energy investment is exposed to different risks (technical, legal, and financial, among
others), there are many ways these risks can be reduced throughout the lifetime of the project. For instance,
technology risk can be reduced by installing proven wind turbines, relying on warranties, and performing
preventive maintenance.
1
Offshore wind projects represented over 50% of the investment activity in clean energy.
2
Median expert response for onshore and fixed-bottom offshore resulting from a study conducted by Berkeley
Lab based on the survey approach: “Forecasting Wind Energy Costs and Cost Drivers”, IEA Wind.

Page 2
This report is organized as follows:
 The Introduction Section provides some background for understanding the global wind market and its
major trends, including the most relevant purposes for which investments are undertaken.
 The following Section provides benchmark values for life cycle costing.
 The Economic Analysis Section discusses and computes different indicators used to measure
profitability, and addresses the importance of the parameters used in the valuation process as well as
sensitivity analysis.
 Finally, the last two Sections discuss risk assessment and mitigation and different financing options.

Page 3
INTRODUCTION
This Application Note is an update of the 2013 publication “Economic Analysis of Wind Projects”. It presents
and illustrates key elements associated with the economic analysis of wind energy projects and is aimed at—
among others—municipalities, cooperatives, investors, and companies that want to install wind parks on their
premises.
It should be noted that this report relates only to multi-megawatt Wind Power Parks (WPPs), since addressing
the small wind sector requires a different approach than the one applied herein. Both onshore and offshore
WPPs are addressed, albeit only fixed-bottom installations within offshore wind (since floating offshore WPPs
are still in under development and not yet market ripe).
Over the past decade, wind energy capacity has increased significantly
3
, due to the growing appetite for clean
and cost-competitive technologies, driven mainly by national support policies. The resulting deployment
enabled technological improvements and cost reductions per unit of installed power.
The driving forces of wind installations are varied in nature:
 Diversification: Wind investments provide a hedge against fuel price shocks and contribute towards
energy independence from third countries.
 Sustainability and responsibility: Increasing environmental concerns, such as climate change,
encourage the installation of clean energy sources such as wind in order to reduce emissions.
 Profitability: A wind project can represent a profitable investment for both investors and financers,
and provides a risk/return profile that in many cases is more attractive than that of other assets (e.g.,
equities market). A case-by-case analysis is required to assess profitability.
On the other hand, there are a number of barriers that are a drag on the growth of the wind sector. These
include:
 Regulatory uncertainty: legislative changes hinder the development of the wind market, given that
investments require predictable revenues.
 Technical challenges: in some markets, the grid is unable to handle the volume of new wind capacity
additions.
According to the Global Wind Energy Association (GWEC), in 2016 new wind power capacity totaled 54.6
gigawatts (GW) worldwide, providing a cumulative installed capacity of nearly 490 GW.
3
An interesting illustration of the evolution of wind installed capacity and its segmentation around the globe
can be reviewed in the Interactive Tool developed by Greenbyte AB with GWEC data available at
http://www.greenbyte.com/resources/evolution-of-wind-power/

Page 4
Figure 1—Global Market Historical Evolution (yearly installations and cumulative capacity) 2008-2016.
More than 40% of the new installed capacity corresponds to WPP installed in China (23.3 GW), a clear leader
of the wind market. Overall, more than 50% of the WPP are located in China and the USA. The following graph
shows the location of the total installed capacity as of 2016.
Figure 2—Global Cumulative Capacity as of 2016 segmented by market.
Of the above capacity, onshore installations account for the great majority (97%). Offshore wind installations
amount to 14 GW of cumulative capacity as of 2016 and nearly 75% of these installations are located in the
UK, Germany, and China. It is expected that in the future the percentage of offshore installations within total
wind capacity will be above the current 3%.
0
10
20
30
40
50
60
70
2008 2009 2010 2011 2012 2013 2014 2015 2016
27.3
Total (GW)
Asia 15.9%
Latin America
0.3%
Pacific Region
46.2%
North America
Africa & Middle East
45.8%
CAGR
08 – 16
-13.6%
38.8 39.7
41.4
45.5
36.5
53.1
64.7
54.6
GW 5.4%Europe
Source: GWEC, CREARA Analysis
121 159 198 239 284 320 372 435 490
Total = 490 GW
35%
17%
10%
6%
5%
3%
3% 2% 2% 2%
16%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
PR China* USA Germany India Spain UK France Canada Brazil** Italy ROW*** Total
Note: * Provisional figures; ** Projects fully commissioned, some grid connections pending; *** Rest Of the World

Page 5
The global wind market is expected to grow at a rate of 10%
4
per year on average from 2017 to 2025, to reach
around 1,180 GW of cumulative wind capacity by 2025.
Figure 3—Global Cumulative Capacity according to market scenarios set by GWEC.
One of the market drivers of wind energy is its cost competitiveness compared to conventional energy
sources. In some cases, wind energy can be competitive per se (i.e., without any governmental support). This
relatively recent phenomenon coincided with the gradual elimination of public incentives such as Feed-in Tariff
(FiT) schemes, and with the introduction of new business models based on market fundamentals such as those
based on Power Purchase Agreements (PPA).
4
Compound Annual Growth Rate (CAGR): calculated as the average CAGR resulting from the 4 scenarios set by
the GWEC.
200
400
600
800
1000
1200
1400
1600
12 13 14 15 16 17E 18E 19E 20E 21E 22E 23E 24E 25E
GWEC 450 Scenario
Moderate Scenario
CAGR
16 – 25E
9.1%
10.7%
Advanced Scenario 7.8%
GW
New Policies Scenario 12.9%
Note: A description of the assumptions within each scenario is available at Global Wind Energy Outlook 2016 (GWEC)

Page 6
Figure 4—Business Model Typical Evolution.
Currently, as subsidies are being reduced, revenues from wind energy projects are increasingly based on
market driven contracts such as PPA rather than on incentive schemes such as FiT. In many cases, revenues
from wind projects are based on PPA revenues plus subsidies, which tend to be market-based (e.g. a premium
over a market price).
Nevertheless, the development of wind energy in different countries shows that it is possible to drive the
market through different models, as long as these are stable and provide predictable revenue streams.
FiT REC ITC / PTC PPA * Spot market
Competitive without any
subsidies
Description
Conditions
Source: CREARA analysis
Note: * PPA are often combined with subsidies such as PTC
• The government pays
the plant owner for
each kWh fed into the
grid
• Contract length is
generally between 20
and 25 years
• Used to reduce
investment
taxes
• Price set per
installed kW
• Every MWh fed into the
grid = a Green
Certificate
• Can be sold to utilities
which need it to reach
quota fixed by the
government
• Contract between
the owner of the
plant and an
electricity consumer
• Used to hedge the
rise of electricity
price in the future
• The electricity
produced is sold
directly to the spot
market
Meaning Feed In Tariff
Renewable Energy
Certificates
Investment/
Production
Tax Credits
Power Purchase
Agreement
Spot market
prices
FiT available and >
spot prices REC available ITC available
PPA price ≤
electricity price Generation parity

Page 7
LIFECYCLE COST COMPONENTS AND BENCHMARKS FOR A WPP
When analyzing wind economics, it is relevant to consider the costs associated to each of the stages of the
lifecycle of a WPP and the ways in which returns can be optimized. With this in mind, this Section includes an
overview of the following main elements:
 Lifecycle stages of a wind energy project: from the initial planning to final decommissioning of the
park.
 Total costs of a WPP: capital investment and operating investment.
LIFECYCLE OF A WPP
The lifecycle of a WPP can be divided in three main stages:
 Project development and installation phase: this ranges from the initial planning to the end of
construction, and generally requires between 6 and 8 years to be completed.
 Operation: it lasts for the entire lifetime of the wind turbine, which in general ranges from 25 to 30
years according to manufacturers.
 End of life: the decommissioning or replacement of the equipment at the end of the WPP’s lifetime.
The next Figure details the activities that are usually performed during each of the main stages in the life of a
wind project:
Figure 5—Wind Project Development by Phases.
To optimize electricity generation during the operation phase of a WPP, three crucial maintenance tasks are
performed: preventive, predictive, and corrective maintenance.
Project stages
Initial planning Permission Financing
Installation &
construction
Operations &
Maintenance
1-2 years
Supplier
management
•Selection of
location
•Tower
installation
•Wind study
•Feasibility
studies
• Apply to
appropriate
public
authority
• Perform the
needed
environmental
studies
• Optimize
project
structure
• Prepare
financial
model
• Investor
recognition
• Identify
suppliers
• Negotiate
terms
• Excavation
• Construction
of WTG
foundations
• Erection of
WTGs
• Installation of
electrical
infrastructure
• Utilization or
sale of energy
produced
• O&M
• Project
management
• Monitoring
2-4 years 2-3 years 1-3 years 1-2 years >20 years
≈6-8 years1
Note: 1Average number of years; project stages can be performed in parallel in some cases
Source: Corporate website; AEE; CREARA analysis
Decommissioning
or replacement
• Remove the
equipment/
retrofitting
>1 years
Project development Operation End of life

Page 8
Table 1—Description of Maintenance Tasks.
Preventive and predictive maintenance jointly require ~40 hours a year per turbine, while corrective
maintenance expenses vary depending on the wind turbine technology being installed: the more reliable the
technology, the lower the non-routine expenses.
In this sense, the lower maintenance costs associated with certain wind turbine designs are regarded as one of
their main advantages. For instance, the corrective maintenance of direct drive technologies (i.e., gearless
turbines) can be less time-consuming than that of other alternatives. In spite of this dispersion, EWEA
estimates that the average time requirements of corrective maintenance can be similar to those required for
preventive plus predictive maintenance.
TOTAL COSTS OF A WPP
To assess the economic viability of a WPP, two of the most important variables
5
are the Capital Expenditure
(CAPEX), which is the initial investment, and the Operational Expenditure (OPEX), which is the sum of the
operating costs of the plant during its life. These variables comprise the total costs associated to the WPP
during its lifetime, term that is generally referred as Life Cycle Cost (LCC). The following Figure illustrates the
case of an onshore WPP with geared wind turbines installed in the US or Europe:
5
Other key variables such as capacity factor will be discussed in a subsequent Section.
Description
Typical tasks
included
Source: Wind Energy Update; CREARA analysis
Preventive
• Change the gear oil, coolants,
seals, brake pads, and filters;
grease the bearings
• Adjust sensors and actuators
• Visually inspect the blades,
tower, and electrical
connections among other
• Preventive or routine
maintenance is a schedule-
based activity performed
typically every six months to
maintain the WPP
Predictive
• Predictive maintenance takes
action when required, and not
according to a pre-fixed
schedule. It aims to detect
anomalies at the earliest
stage possible
• Helps to optimize the stock of
replacement components
• Execute maintenance tasks,
visual inspections, control
measurements, condition
analyses, and repair works
called by a high tech
Condition Monitoring System
(CMS)
Corrective
• Corrective maintenance fixes
detected problems
• The equipment can be
replaced or repaired

Page 9
Figure 6—Life Cycle Cost of an Onshore Installation
6
.
The WTG, which accounts for the largest proportion within the LCC of the wind park, is worth analyzing in
greater detail. The next Figure shows the segmentation of the total cost of a WTG:
Figure 7—Segmentation of Onshore WTG Costs.
It should be noted that total CAPEX for an onshore WPP can vary by up to 50% depending upon variables such
as WTG technology and WPP location.
Until recently, investment costs have been decreasing sharply due mainly to the following reasons:
6
A lifetime of 20 years and an inflation rate of 2% is assumed.
EUR/kW
52%
8%
5%
5%
70%
30%
100%
0
200
400
600
800
1.000
1.200
1.400
1.600
1.800
2.000
WTG
Gridconnection
Construction
Others
TOTALCAPEX
OPEX
LifeCycleCost
Rotor (23% of WTG)
Blades 60.9%
Pitch mechanism and bearings 19.5%
Hub 18.0%
Spinner, nose cone 1.6%
Tower (23% of WTG)
1
Drivetrain (54% of WTG)
Gearbox 20.7%
Mainframe 18.0%
Variable-speed electronics 15.4%
Generator 13.1%
Electrical connection 10.8%
Low speed shaft 5.2%
Yaw drive and bearings 4.6%
Control, safety, and condition monitoring 4.3%
Bearings 3.0%
Hydraulic, cooling system 2.3%
Nacelle cover 2.3%
Mechanical brake, high-speed coupling 0.3%
1
2
3
2
3
Source: NREL; CREARA analysis

Page 10
 The increase in installed capacity driven by policies enabling economies of scale.
 Technological developments that resulted in the rise of WTG average unit capacity, taking better
advantage of available space and decreasing the weight per unit power.
 The introduction of new WTG technologies into the market (such as full converter) that enable better
optimization of wind resources.
On the other hand, operating expenses are those that are incurred over the entire lifetime of the project and
can be grouped as follows:
 Operation & Maintenance costs (O&M), which represent ~60% of OPEX and tend to increase as the
WPP reaches the end of its lifetime.
o The major cost component is the maintenance of the wind turbine generator.
 Other operating costs (~40% of OPEX), including rent, taxes, and insurance.
As was the case with CAPEX, OPEX have also been decreasing on average over time, mainly due to the
expertise gained on O&M tasks and the increase in WTG unit capacity. Current Operating expenses for onshore
wind amount to 40-45 EUR per kilowatt and year on average, compared with fixed-bottom offshore wind of
between 80 and 90 EUR per kilowatt and year
7
.
The total LCC for an offshore wind park can more than double that of an onshore system.
Figure 8—Offshore LCC Segmentation.
Electrical infrastructure and foundations is the most relevant component within offshore wind park CAPEX,
accounting for some 45% of total costs, and increasing in line with distance to shore and water depth. The
following scatter graph illustrates the estimated future developments of offshore WPP in terms of distance to
shore and water depth:
7
“Forecasting Wind Energy Costs and Cost Drivers”, IEA Wind 2016; IRENA 2016.
Source: IRENA 2016,Berkeley Lab 2016,CREARA analysis
EUR/kW
29%
16%
14%
14%
73%
27%
100%
0
1.000
2.000
3.000
4.000
5.000
WTG
Gridconnection
Construction
Others
TOTALCAPEX
OPEX
LifeCycleCost

Page 11
Figure 9—Estimation of Offshore WPPs in terms of Distance to Shore and Water Depth (year 2025).
In particular in the Northern European countries, the available technical potential of far offshore WPP in
addition to the current limited availability of sites near the shore (<20 km), will result in the development of
offshore WPP further away from the coast, which will cause OPEX to increase.
The following figure shows the WTG characteristics expected by 2030
8
(an increase in nameplate capacity, hub
heights and rotor diameter):
8
Results of an expert survey conducted by Berkeley Lab. “Forecasting Wind Energy Costs and Cost Drivers”,
IEA Wind 2016.
WaterDepth(m)
Note: The above is a sample of all offshore WPPs until 2025 (EWEA´s database of offshore WPPs operating, under
construction, consented, in the consenting process or proposed by developers)
Source: EWEA; Eclareon analysis
FarOffshore DeepFarOffshore
DeepOffshore
0
20
40
60
80
100
120
140
160
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
Distance to
shore (km)

Page 12
Figure 10—Expected future characteristics of onshore and offshore WTG.
Scaling in turbine capacity ratings, rotor diameter and hub heights will lead to capacity factor and CAPEX
improvements, two of the main drivers of generation cost reductions. It is estimated that wind generation
costs will decrease by 10%
9
on average by 2020.
9
Ibidem.
Source: “Forecasting Wind Energy Costs and Cost Drivers”,IEA Wind; CREARA Analysis
0
40
80
120
160
0
1
2
3
4
All Europe North
America
Others All Europe North
America
America
Others
2014 Baseline for Germany 2014 Baseline for US 2014 Baseline for fixed-bottom off-shore in Europe
2030 Onshore Capacity (MW) 2030 Onshore Hub Height (m) 2030 Onshore Rotor Diameter (m)
HubHeigth/
RotorDiameter(m)
Turbinecapacity(MW)
0
50
100
150
200
250
0
2
4
6
8
10
12
All Europe North
America
America
America
Others
Turbinecapacity(MW)
2030 Offshore Capacity (MW) 2030 Offshore Hub Height (m) 2030 Offshore Rotor Diameter (m)
HubHeigth/
RotorDiameter(m)

Page 13
ECONOMIC ANALYSIS
To decide whether to invest in a wind project or not, an estimation of the economic value or profitability of the
project is required, which is generally calculated with a financial model. The economic analysis process can be
summarized in three steps:
 First, forecast all the costs and revenues associated to the project during its lifetime and then convert
them to cash flows.
 Then, set different probable scenarios and calculate financial indicators to determine profitability.
 Finally, analyze the results from the perspective of the different holders of capital.
Special care should be taken with setting the assumptions within the analysis that have the greatest impact on
profitability. These are generally related to the following parameters:
 Related to costs, CAPEX and OPEX values, which were detailed in the previous Section.
 Related to revenues, the capacity factor (or full load hours
10
) and the price received (or cost saved) for
the wind electricity generated are the paramount elements.
The capacity (or load) factor of a WPP is the relation between the total amount of energy generated during a
specified period and the potential amount of energy the WPP would produce if it operated at full nameplate
capacity. Therefore, all else being equal, the higher the capacity factor of the WTG in a given wind park, the
higher the electricity-generating potential of that WPP. Clearly, the capacity factor is always lower than 100%
for any generator plant due to unavailability caused by maintenance or repair. In the case of wind power, the
availability of wind also decreases capacity factor.
Capacity factors have improved significantly in recent years. This is a trend that is expected to continue.
 Ten years ago, it was common to have capacity factors between 20-30%.
 Today, it is not uncommon to have wind farms with capacity factors in the range of 30-40% onshore,
and 40-50% offshore
11
.
The above improvement is a result of the new WTG designs, which incorporated larger rotors than before for a
given nominal power, a trend in wind power design emerging in recent years.
Revenues from generated wind electricity can arise from different sources such as:
 The price received through incentive mechanisms such as FiT or market contracts such as PPA (with or
without additional incentives).
 The cost saved by self-consuming wind electricity instead of buying it from the utility grid (although
this is most often the case of small-size wind farms, which are not being addressed in this report).
As explained in a previous Section, revenues based on FiT used to be the norm but are gradually being
replaced by market driven contracts such as PPA
12
as the market matures. Revenues from such contracts
10
Full load hours are equal to capacity factor times the number of hours in an entire year (i.e. 8,760 hours).
11
This varies significantly between locations (for instance, the average is around 25% for onshore in China and
India but 30% in Europe and 40% in North America).
12
This was illustrated in Figure 2: Business Model Typical Evolution.

Page 14
depend upon several variables such as WPP characteristics (size, location, and capacity factor) and the
opportunity cost (e.g., the cost of electricity from the grid). Therefore, different countries (and states within
countries, as is the case of USA) operate with different revenue levels.
Although prices per kWh sold vary significantly, for the purpose of computing the economic viability of a
particular wind project as required in this Section, the revenue per kWh is set here at 7 Euro cents, which is
considered a realistic assumption given the current economics for onshore systems
13
.
Finally, concerning the indicators used to evaluate the economics of the project, the most often used
metrics
14
are computed for a particular wind project.
 Net Present Value (NPV):
o A positive NPV indicates that the project is profitable.
o When choosing between alternative projects, that with the highest NPV should be
undertaken.
 Internal Rate of Return (IRR):
o An IRR higher than the cost of capital indicates that the project is profitable.
o When choosing between alternative projects, that with the highest IRR is not necessarily the
most attractive one; in this case, the NPV rule should be followed.
 Payback period:
o All else being equal, a project is more attractive if the payback period is lower than a
particular desired term.
o This indicator should be used only in conjunction with other metrics, and using discounted
cash flows results in a more accurate, albeit more time-consuming, result.
 Levelized Cost Of Energy (LCOE):
o This metric is widely used to compare between different generation sources.
o The lower the LCOE, the higher the return for the investor.
In addition, for lenders it is paramount to compute the Debt Service Coverage Ratio (DSCR), which is calculated
as the cash flows available to cover debt service expenses divided by interest and principal payments.
In order to compute the above financial indicators, the following assumptions were set:
Concept Unit Value
WPP size MW 21
WTG size MW 1.5
WTG technology - DFAG
15
Full load hours Hours/year 2,628
13
Average prices resulting from auctions have decreased significantly in recent years: from USD 80 in 2010 to
USD 40 per MWh in 2016 (IRENA, 2017). Although the average price resulting from 2016 auctions is well below
70 Euro/MWh, herein it is considered a reasonable price to reflect in a simplified way the economics of
business models based on PPA prices plus potential additional revenues (e.g. tax credits such as PTC in the US
can amount to EUR 20 per MWh).
14
For a complete definition of these financial indicators, visit Leonardo Energy Website’s Application Note on
the subject (‘LIFE CYCLE COSTING—THE BASICS’, February 2012).
15
Doubly Fed Asynchronous Generator, the most commonly used model.

Page 15
Concept Unit Value
Construction date Date 2017
Investment accounting life Years 15
WTG service life Years 20
WACC % 6
Leverage % 80
Inflation % 2
Feed-in tariff €/MWh 70
Tax rate (over EBIT) % 30
Indicative CAPEX
16
€/kW 1,341
Indicative OPEX €/kW/year 40
Working Capital Requirements € 0
17
Table 2—WPP Characteristics and Project Assumptions.
It should be noted that to evaluate the economics of the project, here it is performed from the point of view of
the project in its entirety (including debt and equity holders), i.e., project cash flows and the Weighted
Average Cost of Capital (WACC)
18
is used. Overall, estimated project IRR can range from 7% to 10% while equity
IRR can range from 10% to 15%.
INTERNAL RATE OF RETURN
Many investors will be interested in calculating the IRR, which is the project break-even rate of return, and as
such, should be greater than the required rate of return (or cost of capital).
An analysis of the project rate of return involves several assumptions that might not hold. Therefore, in order
to determine the impact on IRR of a change in the main assumptions of the financial model, three scenarios
were set, each with a similar probability of occurrence:
 Base Case: it includes conservative estimates of the variables used to compute profitability.
 Low Case: it includes low range values with respect to what was previously assumed in the Base Case.
 High Case: it includes high range values with respect to the Base Case.
The set of assumptions are as follows:
Variable Low Case Base Case High Case
Full load hours 2,100 2,628 3,000
OPEX (€/MW/year) 30,000 40,000 50,000
CAPEX (k€/MW) 1,100 1,341 1,600
Revenue
19
(€/MWh) 50 70 90
Table 3—Estimates for the Sensitivity Analysis.
The results below give an overall perspective of the impact of the variables analyzed in the profitability of the
project:
16
With the purchase of the WTGs, a full service warranty of 2 years is included.
17
Average invoice collection period and average invoice payment period are considered equal (both 45 days).
18
For a complete explanation on the derivation of WACC, please refer to www.thatswacc.com.
19
For the sake of simplicity, it is assumed that revenues are based on FiT.

Page 16
Figure 11—One-way Sensitivity Analysis of WPP Parameters.
As the above Figure illustrates, the profitability of the wind investment analyzed herein varies greatly
depending upon the assumptions. An 80% increase in FiT (from 50 to 90 €/MWh) results in an IRR almost three
times higher. In contrast, OPEX appears as the least influential IRR variable of the four.
NET PRESENT VALUE
Many investors also compute the NPV, which is a very popular method for computing the value generated by
long-term projects, either for all the holders of the capital (equity and debt) or just for the equity holders.
Here, the former will be computed.
From the previous sensitivity analysis, it was concluded that IRR varies the most as a result of a change in
revenue levels per kWh. By definition, NPV and IRR are closely related, as the IRR is the rate of return that
makes the NPV of the project equal to zero. Therefore, all else being equal, it can be asserted that, of the
parameters included in the analysis, the revenue levels will be the variable with the greatest impact on NPV as
well. Assuming a 6% WACC, the resulting NPV improves from the low case (with a negative NPV) to the high
case:
Full load hours
OPEX
CAPEX
Project IRR
FiT
X 2X 3
4%
6%
8%
10%
12%
14%
Low Case Base Case High Case

Page 17
Figure 12—NPV of the Project Depending on FiT Levels.
This result shows that in the low case scenario, the project should not be undertaken, while in the base and in
the high scenario, the project reaches profitability, albeit creating more than twice the value in the high case
than in the base case.
PAYBACK PERIOD
As opposed to the metrics computed above, the payback period does not address profitability but only gives
an indication of the liquidity of the project. This tool is relatively simple to calculate and intuitive for those
investors interested in knowing the time required to recover the initial investment.
Generally, the calculation of the payback period compares the undiscounted cash flows generated by the
project with the investment cost, in order to provide an estimate of the length of time required to recover the
investment. With this relatively simple calculation, there is no consideration of the time value of money.
A more accurate and conservative approach would consider the estimated discounted cash flows, since the
undiscounted payback period is usually lower than the discounted payback period
20
.For the wind project used
as case study in this report, both methods have been calculated and results are as follows:
 Using discounted cash flows: 14 years.
 Using undiscounted cash flows: 9 years.
The Following Figure illustrates the annual free cash flows as well as the accumulated discounted cash flows
under the base case scenario:
20
That is, as long as the cost of capital is greater than 0%.
-2.223
19.638
-4.000
1.000
6.000
11.000
16.000
21.000
8,707
High Case
Base Case
Low Case
NPV(k€)

Page 18
Figure 13—Payback Period of the Base Case Scenario.
LEVELIZED COST OF ENERGY
This metric is particularly useful for those investors seeking to compare different generation sources. The
Levelized Cost of Energy (LCOE) can be defined as the constant and theoretical cost of generating one MWh of
wind electricity, whose present value is equal to that of all the total costs associated with the wind system
over its lifespan. As such, it is characterized by the following factors:
 The LCOE accounts for all costs associated with a WPP over its life, which include initial investment,
O&M, and taxes, among others.
 It assumes a constant value per year and is expressed as cost per kWh.
 It incorporates total wind electricity generated over the entire lifespan of the WPP.
 It considers the return required from the investment, to discount future costs (and production) to
present.
The following equation shows the resulting identity for the computation of LCOE from the perspective of
capital providers (debt and equity holders):
EQUATION 1: LCOE CALCULATION (1)
∑ (
𝑳𝑪𝑶𝑬 𝒕
(𝟏 + 𝒓) 𝒕
× 𝑬𝒕)
𝑻
𝒕=𝟏
= 𝑰 + ∑
𝑪 𝒕 × (𝟏 − 𝐓𝐑)
(𝟏 + 𝒓) 𝒕
𝑻
𝒕=𝟏
− ∑
𝑫𝑬𝑷 𝒕 × 𝐓𝐑
(𝟏 + 𝒓) 𝒕
𝑻
𝒕=𝟏
Where:
 LCOE (EUR/MWh): Levelized Cost of Electricity
 T (Years): Economic lifespan of the Wind system and t is Year t
 Ct (EUR): Operation & Maintenance (O&M) costs in year t
 Et (MWh): Wind generated electricity in year t
 I (EUR): Initial investment
 r (%): Nominal discount rate (WACC)
 TR (%): Corporate Tax rate
kEUR
Accumulated discounted
free cash flows
Free cash flows
Source: CREARA Analysis
Simple payback period = 9 years
-30.000
-25.000
-20.000
-15.000
-10.000
-5.000
0
5.000
10.000
15.000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Discounted payback period = 14 years
Accumulated free cash flows

Page 19
 DEP (EUR): Depreciation for tax purposes
Assuming a constant value per year, LCOE can be derived by rearranging Equation 1:
EQUATION 2: LCOE CALCULATION (2)
𝑳𝑪𝑶𝑬 =
𝑰 + ∑
𝑪𝒕 × (𝟏 − 𝑻𝑹)
(𝟏 + 𝒓)𝒕 − ∑
𝑫𝑬𝑷𝒕 × 𝑻𝑹
(𝟏 + 𝒓)𝒕
𝑻
𝒕=𝟏
𝑻
𝒕=𝟏
∑
𝑬𝒕
(𝟏 + 𝒓)𝒕
𝑻
𝒕=𝟏
When the cost of generating a kWh of wind energy (i.e. the LCOE) is equal or below the cost of an alternative
energy source, it can be said that wind energy is cost-competitive. Even if wind LCOE is above the current price
of alternative sources, it should be noted that wind PPA contracts allow the offtakers to secure a long-term
price of wind electricity rather than buying it from the grid, at an uncertain (and arguably increasing) rate.
A case-by-case analysis is required to perform a thorough LCOE analysis, for the following reasons:
 LCOE results are highly sensitive to assumptions.
 Assumptions should be consistent across technologies.
In order to analyze the impact that the different parameters have on the LCOE, a sensitivity analysis was
performed according to 3 different scenarios:
 Base Case: it includes conservative estimates of the variables used to compute profitability.
 Low Case: it includes low range values with respect to what was previously assumed in the Base Case.
 High Case: it includes high range values with respect to the Base Case.
Variable Low Case Base Case High Case
Full load hours 2,100 2,628 3,000
Discount Rate 4% 6% 8%
CAPEX (k€/MW) 1,100 1,341 1,600
Table 4—Estimates for the Sensitivity Analysis.
The results are as follows:

Page 20
Figure 14—One-way Sensitivity Analysis of Three Parameters on Onshore Wind LCOE.
The above illustration shows that the parameters used in the financial model have a significant impact on
LCOE: considering the assumptions made, LCOE can be 40% higher in the most pessimistic scenario when
compared to the most optimistic one.
Two trends have been mentioned in previous Sections that will invariably result in a lower wind LCOE in the
future:
 Lower CAPEX as a result of lower WTG costs.
 Higher capacity factor that will result in greater output efficiency.
 Lower cost of financing, which would result in lower WACC.
€/MWh X 1.4
Source: CREARA Analysis
35
40
45
50
55
60
65
Low Case Base Case High Case
Full Load hours
WACC
EPC costs

Page 21
RISK ASSESSMENT
Wind projects are not risk-free. Throughout a project’s life cycle, it is exposed to political, financial,
technological, and other risks. The main risks are identified in the following Figure:
Figure 15—Main Risks of a Wind Project.
The technology risk is the risk of inherent technological failures. It will depend on the WTG technology
installed. The technology risk is one of the most important, as it can have a highly negative influence on both
the start-up and O&M risks. By installing proven technologies, relying on warranties, and performing predictive
maintenance, technology risk can be reduced.
The following Figure shows the average downtime per component during failure and the frequency of failures.
Figure 16—Component Reliability and Downtime Average.
As the above Figure illustrates, when the gearbox or generator fails, the turbine is out of service for a relatively
long period while these components are being repaired. This is downtime that negatively affects project
profitability.
Development O&M
• Termination risk • O&M risk
• Wind resource risk
• Energy price risk
• Start-up risk
• Administrative risk
• Political and regulatory risk
• Technology risk
• Interest rate risk
Drive train
Supporting Structure/ Housing
Generator
Gearbox
Rotor Blades
Mechanical Brake
Rotor Hub
Yaw System
Hydraulic System
Sensor
Electronic Control
Electrical System
-8 -6 -4 -2 0 2 4 6 81 0.75 0.5 0.25
Source: ISET;IWET; CREARA research; CREARA analysis
Days of downtime/failureAnnual failure frequency

Page 22
In conclusion, all risks should be identified, quantified, and mitigated to seek to ensure the profitability of the
project. The overall risks within a wind power project and mitigation examples are summarized in the following
Table:
Table 5—Risk and Mitigation Examples.
Apart from the above examples, there are other mechanisms to reduce risk, which are paramount for the
success of the investment:
 Setting conservative assumptions in the financial model of variables such as:
o Inflation estimates
o Operating expenses
o Revenue estimates
 Performing sensitivity analysis of parameters such as the ones mentioned above.
Risks Main mitigation
• Turnkey contract with closed price and terms
• Viability of the project developer
• Delivery warranty
• Insurance coverage
• Turnkey contract with closed price and terms
• Viability of the project developer
• Legal advice
• Stable regulatory framework
• Insurance coverage
Construction and start-up
risks
Administrative risks
Political and regulatory risk
Technology risk • Warranties
• Installing proven technologies
Wind resource risk
• Historical data
• Resource analysis with probabilities
O&M risk • O&M contract with guarantees and penalties
Interest rate risk • Fixed interest rates through contracts

Page 23
FINANCING ALTERNATIVES
Wind energy projects are generally structured with high leverage, thanks to the relatively predictable and
stable nature of future cash flows.
With the recent global financial crisis (and the associated tight financing conditions) being behind us, appetite
for wind investments has increased in the past years, leading to higher availability of capital at lower interest
rates. According to WindEurope, wind energy investments in Europe increased a 5% in 2016 with respect to
2015 (totalling €27.5bn of new investments in wind energy in 2016). Wind investments accounted nearly 90%
of the new renewable energy finance in 2016, compared to almost 70% in 2015.
Financing costs depend on the regulatory framework (the more stable, the lower the financing costs) and the
local risk assessment (i.e. level of accuracy in estimates, risk management practices, industry experience, etc.).
It is expected that financing cost reductions will be important drivers for cost reductions in offshore wind, due
to its lower level of market maturity (with respect to onshore). Moreover, in less-developed wind markets,
improvements in financing are more likely than in relatively more mature markets.
There are two main long-term financing alternatives for a multi-megawatt WPP: corporate loan or project
finance.
Corporate Loan
 Financial institutions lend capital on the basis of the creditworthiness of the company or the investor.
o As such, the bank is unlikely to be affected by a hypothetical insolvency of the project, since
it is the company or the investor who backs up the loan.
 The borrowed capital generally ranges between 50-100% of the total investment (leverage rate).
 In contrast to project finance, it is not necessary for the financial institution to perform a Project Due-
Diligence; it is only required that the consolidated financial statements of the parent company be
analyzed.
 The cost of financing varies depending on the tenor, the characteristics of the borrower, et cetera.
Project Finance
 Project financing relies only on the cash flows generated by the project in order to repay the loan, not
on other assets the borrower may possess.
o The project by itself must be able to guarantee the repayment of debt even under negative
scenarios.
 Financial institutions lend capital to a Special Purpose Vehicle (SPV).
 For this lack of recourse to the parent company, project financing is more expensive than corporate
financing.
 Leverage under project finance ranges between 70-80%, depending on the project and the country.
Project finance consists of several stages, within which the pre-financial stage is the most critical one since it
will determine if the project will be financed or not.

Page 24
Figure 17—Project Finance Stages.
Pre Financing stage Financing stage Post Financing stage
• Project identification
• Risk identification &
minimizing
• Technical and financial
feasibility
• Equity arrangement
• Negotiation and syndication
• Commitments and
documentation
• Disbursement
• Monitoring and review
• Financial closure/Project
closure stage
• Repayments & Subsequent
monitoring
Source: Corporate website; CREARA analysis

Page 25
CONCLUSION
The following principal conclusions can be drawn from this report:
 Wind investments can provide an attractive risk/return profile, as well as other potential benefits
such as risk diversification and a hedge against rising fuel prices.
o For instance, it is currently more profitable for some electricity consumers to secure a fixed
long-term price for wind electricity through a PPA, rather than buying electricity from the
grid.
 Nevertheless, in order for wind projects to be viable, it is necessary that the business model be based
on a stable scheme that enables long-term predictable revenue streams, regardless of whether it is
market driven (PPA) or politically driven (FiT).
 In all cases, an economic analysis of the investment opportunity is required before undertaking the
project.
o Several financial indicators are useful for assessing the viability of the project, such as IRR,
NPV, and payback period.
o It is advised that conservative assumptions be used in the financial model and sensitivity
analysis be performed in order to consider the impact of different scenarios on profitability.
 Financing costs depend on the regulatory framework (the more stable the regulatory framework
remains, the lower the financing costs) and the local risk assessment (which depends on the level of
maturity of the market).
o Predictable and stable cash flows allow investors to benefit from high leverage, mainly
through corporate financing or project financing.
 Finally, even though a wind energy investment is exposed to different risks throughout the lifetime of
the project, there are many ways in which these risks (technical, legal, and financial, among others)
can be reduced.
o For instance, technology risk can be reduced by installing proven wind turbines, relying on
warranties, and performing preventive maintenance.

Page 26
ANNEX: ACRONYMS
Acronym Meaning
CAGR Compound Annual Growth Rate
CAPEX Capital Expenditure
CMS Condition Monitoring System
DFAG Doubly Fed Asynchronous Generator
DSCR Debt Service Coverage Ratio
EBIT Earnings Before Interest and Taxes
EPC Engineering, Procurement and Construction
EPRI Electric Power Research Institute
EU European Union
EURIBOR European Interbank Overnight Rate
EWEA European Wind Energy Association
FiT Feed In Tariff
GWEC Global Wind Energy Council
IRR Internal Rate of Return
kWh Kilo Watt Hour
LCC Life Cycle Cost
LCOE Levelized Cost of Energy
NPV Net Present Value
NREL National Renewable Energy Laboratory
MW Mega Watt
MWh Mega Watt Hour
O&M Operation & Maintenance
OPEX Operational Expenses
PPA Power Purchase Agreement
ROE Return On Equity
SPV Special Purpose Vehicle
WACC Weighted Average Cost of Capital
WPP Wind Power Park
WTG Wind Turbine Generator

Economic analysis of wind projects

More Related Content

What's hot

Similar to Economic analysis of wind projects

More from Leonardo ENERGY

Recently uploaded

Economic analysis of wind projects