Conference PaperPDF Available

Benefits of Measuring the Wind Resource - How Value is Created for the Windfarm

Authors:
Conference Paper

Benefits of Measuring the Wind Resource - How Value is Created for the Windfarm

Abstract and Figures

Currently the cost of the traditional solution for offshore wind measurement, a hub-height lattice met mast on a fixed foundation within the windfarm boundary, has become extortionately expensive, primarily due to a number of factors, which include: • the deeper waters at current project sites, • the more severe wave climates at current project sites, • the vessels able to work under such conditions including • the mobilisation costs for a one-off operation. However an accurate knowledge of the wind resource allows improved decision making and reduces risk, in terms of the windfarm design as well as the investment decision; for the investment decision, risks to project finance also need to be considered. A suitable designed measurement campaign delivers a positive NPV, since the financial return required is lower on a less risky investment. This risk reduction can be quantified via different means, depending upon the project structure. A widely understood approach is the improvements in the project finance conditions that a lender would grant to the project, specifically how much project debt can be offered. Figure 1 presents the normalised NPV for leading candidate wind measurement strategies for an offshore wind farm scenario: • the reference case is to make no measurements and to use a regional wind atlas, preferably based on a multitude of source including satellite data, measurements where available and mesoscale analyses; i.e. methodology such as described in reference [2]; • if a nearby windfarm has a met mast with a number of years of data, this may well deliver significant value; • a new conventional met mast on a fixed foundation has been the default wind measurement strategy to date but will be expensive; it will deliver high quality measurement data, subject to appropriate design and operation; • a LiDAR unit on a light-weight jacket (termed LiGA within this paper) will be a lower cost strategy; LiDAR has become widely acceptable as the primary source of windspeed measurements, for both onshore and offshore sites; the viability of the structure is subject to suitable ground conditions; • the vertical LiDAR measurements could be augment by horizontal measurements with a scanning LiDAR for a relatively low additional cost, thus providing data on variation of windspeeds across the windfarm site; note that a single location of measurement means that only radial rather than full 2D vector wind-fields can be determined, thus reducing the value of the campaign compared with a full dual unit strategy; • a number of floating LiDAR concepts are currently under development, including undergoing field testing; the relatively low cost and rapid deployment possible makes such a strategy highly attractive however currently widespread acceptance across the investment community and their advisers is currently lacking, hence deployment as primary source of wind measurement data introduces strategic risk; • if the windfarm site is located close to the coast, within the range of scanning LiDAR units located at the shoreline, it would be possible to measure the full wind-field across the windfarm site; the advantages of lower costs and rapid deployment are countered by disadvantages of lack of trials, a prerequisite for commencing route towards widespread acceptance within the investment community. Clearly the project characteristics as well as uncertainty assumptions will drive the value creating by candidate wind measurement strategies and Figure 1 presents the results for just one example of an imaginary offshore windfarm. Details of the underlying assumptions are presented in the main body of the paper. A benchmarking exercise was also undertaken against a bona-fide windfarm project Financial Model, which delivered good agreement. Finally, under typical conditions, increasing the certainty regarding any project in a development portfolio will also deliver benefits to the portfolio as a whole, allowing: • prioritisation of projects during the development phase • selection of projects for realisation at FID An indicative analytical model was developed to undertake a preliminary investigation of potential scale of such benefits which suggested these could be in the order of €10m. Note that this principal will apply to any portfolio, whether solely of offshore wind projects, or of a mix of offshore wind projects together with other investment opportunities.
Content may be subject to copyright.
Benefits of Measuring the Wind Resource
How Value is Created for the Windfarm
DONG Energy Wind Power
DONG Energy Andrew Henderson
European Wind Energy Conference
Barcelona, Spain
11th March 2014
Method: Uncertainty and Value
2
Introduction
Outline of Presentation
Candidate Wind Measurement Strategies and Cost-Benefit Analysis
Value of Portfolio
Summary and Conclusions
2012 RESULTS AND 2020 STRATEGY
Method: Uncertainty and Value
4
Introduction
Outline of Presentation
Candidate Wind Measurement Strategies and Cost-Benefit Analysis
Value of Portfolio
Summary and Conclusions
Wind Measurements Offshore
Current Status
Overview
around 50 met masts built in the seas
around Northern Europe
majority on monopile foundations in
shallow waters
the "reference standard" for wind
resource assessment offshore
Challenges
many of the current projects are in
deeper waters
larger support structure required
more severe metocean climate, impacts:
ground conditions surveys
design
installation
availability of vessels
characterising large areas typical of
some modern offshore windfarms /
windfarm clusters
costs have risen by x10
5
Method: Uncertainty and Value
Principal
Reduced Uncertainty is More Valuable
portfolio effect
savings accounts / bonds vs. more
volatile stock market
this is different from the principal of Greater Reliability
being more valuable
Method
assume project is Project Financed
(debt funded)
debt is sized on free-cash flow based
on P90 energy production
If Greater Certainty of Wind resource,
→ Higher P90 energy production
Higher P90 income
→ Greater debt available
→ Higher Return on Equity
Note that DONG Energy does not use debt funding
for offshore windfarm projects currently; however
our Investment Partners do, as do many other
developers.
6
Candidate Wind Measurement Strategies
numerical desk-top studies
mesoscale
remote sensing
satellite
shoreline measurements
met mast
LiDAR
portfolio methods
on-site met mast
fixed
floating
on-site LiDAR
bespoke fixed structure
existing structure i.e. oil & gas
floating
7
Outline Measurement Campaign Programme
for fixed Met Mast (sMP) on shallow-water Monopile (~25m)
Sources of Uncertainty
Objective is to Minimise in a Cost-Effective Manner
Wind
Temporal Variation; typical
assumptions:
6% annual standard deviation
uncorrelated
Spatial Variation
greatest variation and uncertainty at the
coastal zone
hence impracticality of measuring
onshore
Vertical Variation
Measurements
instrument precision
flow distortion
met mast
adjacent structures, i.e. on O&G platform
correlation with suitable long-term
record
8
Chris Garrett
No Measurements
Reference for Assessment of Candidate Wind Measurement
Strategies
Wind Atlas / Desk-top analysis of portfolio of sources
assume gross uncertainty of 7.5%
arguably low, hence valuations of alternatives could in reality be higher
9
Method: Uncertainty and Value
10
Introduction
Outline of Presentation
Candidate Wind Measurement Strategies and Cost-Benefit Analysis
Value of Portfolio
Summary and Conclusions
Existing Met Mast in the Vicinity
cost of measurement campaign
encourages sharing of met masts
if available, highly attractive option
since also can increase length of
measurement campaign (subject to
construction of adjacent windfarms)
11
Fixed Met Mast
conventional approach
around 30 installed across Europe
another 5 installed last couple of years
effectively similar strategy as onshore
costs have risen from ~1m to ~10m
deeper waters → need for high-
specification installation plant
tight market conditions
Potential Approach: Installation-
Optimised Strategy
majority of cost is installation-related
combine with other windfarm installation
align design with windturbine foundations
inevitably increased procurement costs
aim for significant reduction in
mobilisation / demobilisation
i.e. reuse of sea-fastening
mast lift will be bespoke
12
LiDAR on Light-weight Jacket
Jacket on Suction Caisson Foundation
requires suitable soils
alternative: GBF
Loads from a LiDAR unit significantly reduced compared with a
met mast
Optimised operating life
i.e. 5 years rather than 25 years
Increased Value if Scanning LiDAR installed
can be redeployed
13
suitable ground conditions
required
alternative foundation
variants possible
Floating LIDAR
rapid deployment; reduced
requirements for:
geotechnical survey
consent type
LiDAR technology itself has gained
widespread acceptance
also now offshore on fixed platforms
impact of floater motion on LiDAR unit
reliability to be proven [i.e. as per the
generic offshore risk]
14
DONG Energy FLiDAR at Burbo Banks
Method: Uncertainty and Value
15
Introduction
Outline of Presentation
Candidate Wind Measurement Strategies and Cost-Benefit Analysis
Value of Portfolio
Summary and Conclusions
Portfolio Benefits
Greater knowledge of the wind resource
will deliver:
Improved understanding of the project
Improved Decision-making across the
portfolio
Applies to any typical portfolio where
there are:
different opportunities of broadly similar
attractiveness
ability for some redeployment of capital,
either between projects or between
sectors
16
Method: Uncertainty and Value
17
Introduction
Outline of Presentation
Candidate Wind Measurement Strategies and Cost-Benefit Analysis
Value of Portfolio
Summary and Conclusions
Summary and Conclusions
Wind Measurements deliver concrete value to offshore windfarms
Met masts remain cost-effective at today's installation prices
however development risk?
several potentially attractive new technologies on the horizon
18
Thank you for your Attention
Contributions from this
authors and contributors is
acknowledged and ap
Miriam Marchant
Hug
Mart
K
Rém
Fe
19
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 1
10 - 13 March 2014
Wind measurements campaigns offshore
how they create value for windfarms
Andrew Henderson
Rémi Gandoin
Miriam Marchante Jimémez
Hugh Yendole
Martin Méchali
DONG Energy Windpower; 33 Grosvenor Place, London SW1X 7HY
; +44 207 811 5416
0. Executive Summary
Currently the cost of the traditional solution for offshore wind measurement, a hub-height lattice
met mast on a fixed foundation within the windfarm boundary, has become extortionately
expensive, primarily due to a number of factors, which include:
the deeper waters at current project sites,
the more severe wave climates at current project sites,
the vessels able to work under such conditions including
the mobilisation costs for a one-off operation.
However an accurate knowledge of the wind resource allows improved decision making and
reduces risk, in terms of the windfarm design as well as the investment decision; for the
investment decision, risks to project finance also need to be considered.
A suitable designed measurement campaign delivers a positive NPV, since the financial return
required is lower on a less risky investment.
This risk reduction can be quantified via different means, depending upon the project structure.
A widely understood approach is the improvements in the project finance conditions that a
lender would grant to the project, specifically how much project debt can be offered.
Figure 1 presents the normalised NPV for leading candidate wind measurement strategies for
an offshore wind farm scenario:
the reference case is to make no measurements and to use a regional wind atlas,
preferably based on a multitude of source including satellite data, measurements where
available and mesoscale analyses; i.e. methodology such as described in reference [2];
if a nearby windfarm has a met mast with a number of years of data, this may well deliver
significant value;
ANHEN@DONGEnergy.co.uk
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 2
10 - 13 March 2014
a new conventional met mast on a fixed foundation has been the default wind measurement
strategy to date but will be expensive; it will deliver high quality measurement data, subject
to appropriate design and operation;
a LiDAR unit on a light-weight jacket (termed LiGA within this paper) will be a lower cost
strategy; LiDAR has become widely acceptable as the primary source of windspeed
measurements, for both onshore and offshore sites; the viability of the structure is subject to
suitable ground conditions;
the vertical LiDAR measurements could be augment by horizontal measurements with a
scanning LiDAR for a relatively low additional cost, thus providing data on variation of
windspeeds across the windfarm site; note that a single location of measurement means
that only radial rather than full 2D vector wind-fields can be determined, thus reducing the
value of the campaign compared with a full dual unit strategy;
a number of floating LiDAR concepts are currently under development, including
undergoing field testing; the relatively low cost and rapid deployment possible makes such a
strategy highly attractive however currently widespread acceptance across the investment
community and their advisers is currently lacking, hence deployment as primary source of
wind measurement data introduces strategic risk;
if the windfarm site is located close to the coast, within the range of scanning LiDAR units
located at the shoreline, it would be possible to measure the full wind-field across the
windfarm site; the advantages of lower costs and rapid deployment are countered by
disadvantages of lack of trials, a prerequisite for commencing route towards widespread
acceptance within the investment community.
See Table 10 for commentary on Technology Maturity
LWJ = Light-weight jacket, or LiGA
Figure 1: Overview of Wind Measurement Strategy Value
Clearly the project characteristics as well as uncertainty assumptions will drive the value
creating by candidate wind measurement strategies and Figure 1 presents the results for just
one example of an imaginary offshore windfarm. Details of the underlying assumptions are
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 3
10 - 13 March 2014
presented in the main body of the paper. A benchmarking exercise was also undertaken
against a bona-fide windfarm project Financial Model, which delivered good agreement.
Finally, under typical conditions, increasing the certainty regarding any project in a development
portfolio will also deliver benefits to the portfolio as a whole, allowing:
prioritisation of projects during the development phase
selection of projects for realisation at FID
An indicative analytical model was developed to undertake a preliminary investigation of
potential scale of such benefits which suggested these could be in the order of €10m. Note that
this principal will apply to any portfolio, whether solely of offshore wind projects, or of a mix of
offshore wind projects together with other investment opportunities.
1. Approach and Method
A bespoke wind-finance model has been developed to estimate the benefit of undertaking wind
measurement campaigns through in the improved conditions
.
The principles behind the Provision of Non-recourse Project Debt are:
1. Windfarm must be able to cover any debt repayments from within the windfarm’s own cash-
flow and with a suitable margin, called the Debt Service Coverage Ratio (DSCR)
a. This is the ratio between the anticipated free cash-flow once all operating costs are
covered and the debt repayment
b. This ratio depends on the uncertainty scenario, hence a lower DSCR is required for the
P90 than for the P50 energy estimate case
2. The difference between the P90 and P50 energy production estimates will depend on the
uncertainties, including that of the long-term average windspeed at the site
a. The P90 is generally the driving criterion when determining debt levels for pre-
operational projects; this is because the uncertainty will invariably be relatively high
b. A higher P90 figure means more debt can be provided, hence improving the project
economics from the equity investors perspective
3. Hence to estimate the benefit of onsite wind measurements, modelling of the following is
needed:
a. Impact of wind measurements undertaken on project uncertainty, i.e. how has the
uncertainty reduced and hence the P90 figure increased, once the wind measurement
device (i.e. met mast) has been installed and operating for a period (i.e. one, two or
three years etc.)
b. The resulting increase in provision of non-recourse debt for the project and hence the
improvement in the project’s financial metrics: i.e. IRR or NPV
For this analysis, a number of assumptions for a generic offshore windfarm have been made,
the most important of which are presented in Table 1 below.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 4
10 - 13 March 2014
Table 1: Approach and Method - Key Assumptions for Evaluation
Assumption
Value
Comment
Capacity 700MW Capacity driven by two 220kV export cables, including
windturbine generation capacity optimisation
CapEx €3.00m/MW Assumes progress in reducing costs
Tariff €125/MWh Applicable for first 15 years of operations; market price of
€50/MWh for final years of operation
Windspeed 9.5 m/s Mean value; Weibull distribution assumed
Cost of Equity 30%/15%/12% During development / construction / operation respectively;
for modelling purposes only
Cost of Debt 5.5% Variable, in particular depending on project characteristics,
financing structure and lender’s appetite; for modelling
purposes only; source [1]
Debt Service
Ratio 1.35 against P90 revenues, as anticipated at FID
1.1 Benchmarking of Modelling Approach
The approach has been benchmarked against the financial model used in a recent transaction.
The discrepancy between the two models in terms of NPV uplift at FID was less than 25%,
which must be considered to be acceptable. No review of the cause of this discrepancy has
been undertaken however potential reasons include:
the necessary simplifications in the financial modelling aspects within the analysis tool used
for this paper and
the differences between the estimated assumptions used for this paper, i.e. Table 1, and
the confidential values used in the real project financial model.
2. Valuation of Candidate Wind Measurement Strategies
2.1 Wind Atlas (Desk-top Study)
An immediate estimate of the wind resource at any site can be made using a wind atlas; for
greatest accuracy this should be derived from a composite of measurements and models, such
as satellite measurements, offshore met masts in the vicinity, mesoscale modelling, reanalysis
(long-term) etc.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 5
10 - 13 March 2014
Table 2: Wind Atlas (Desk-top Study) - Key Assumptions for Evaluation
Assumption
Value
Comment
Wind speed Uncertainty § 7.5%
Actual value will depend on level of data and
quality and proximity of calibration points; this
value is arguably low (unconservative);
consequentially benefits of measurement
campaign would be higher than presented in
Figure 1
Cost ~ Zero
Timing Immediate
§ = combined
This scenario is used as the reference for analysis. Figure 2 shows that for this scenario,
obviously improved knowledge of the wind resource is only gained once the windfarm
commences production.
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 2: Evolution of Wind Resource Uncertainty - Wind Atlas (Desk-top Study)
If an offshore wind mast is located in the vicinity and the topography of any nearby shorelines is
flat, the uncertainty would be lower, i.e. effectively evolving into the following "Neighbouring
Offshore Met Mast" strategy.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 6
10 - 13 March 2014
2.2 Met Mast in a Neighbouring Windfarm
Access to an existing offshore met mast in the vicinity will allow a more accurate estimate of the
windspeed to be made, depending on:
[1] distance from shore (windfarm and mast)
[2] distance between windfarm and met mast
[3] complexity of any nearby land terrain
[4] extent of knowledge of the local wind-regime
Table 3: Met Mast in a Neighbouring Windfarm - Key Assumptions for Evaluation
Assumption Value Comment
Horizontal Uncertainty 4.0% Highly dependent on distances
Duration 5 years
Cost Negotiable Assumed zero for purposes of analysis; i.e.
developer has access due to ownership of project
or arrangement with
Timing Immediate Depends on project development maturity of
neighbouring project
Figure 3 presents the measurement campaign programme, which delivers significantly reduced
uncertainty at FID, Figure 4, compared with the no mast assumption (Figure 2). Typically there
will be costs associated with procurement of this data, unless a quid-pro-quo arrangement can
be reached, however this is ignored for the purposes of this analysis.
Figure 3: Programme - Met Mast in a Neighbouring Windfarm
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 7
10 - 13 March 2014
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 4: Evolution of Wind Resource Uncertainty - Met Mast in a Neighbouring Windfarm
2.3 New Conventional Met Mast
A conventional lattice tower met mast on a monopile or other suitable foundation has historically
been the preferred wind measurement strategy, with around fifty units, including now
decommissioned masts, located across Northern Europe. This type of equipment will measure
at a single point within the windfarm and hence uncertainty remains regarding the variation
across any large windfarm or if the site is close to shore.
Table 4: New Conventional Met Mast - Key Assumptions for Evaluation
Assumption Value Comment
Horizontal Uncertainty 2.0% Due to size of windfarm
Cost Very High
Timing 2 years Requires geotechnical survey
As water depths at windfarm development sites have increased over recent years, the
deployment of large installation plant have become necessary for the construction works, due to
the deep waters, more severe wave regimes as well as the heavier foundation structures.
These vessels have high day-rates, exacerbated by any tight market conditions, which will be
due during construction as well as the several weeks of mobilisation and demobilisation.
The consequence has been that deployment costs for offshore met masts have risen by a factor
of ten over the past decade and installation may contribute over half the cost of a new met
mast, as illustrated in Figure 5.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 8
10 - 13 March 2014
Figure 5: Indicative Conventional Met Mast Cost breakdown
With installation contributing such a large part of the overall cost, savings should be realisable if
attention was focused on minimising installation costs rather than implicitly the weight of steel.
An "installation-optimised design" could be based on the following principles:
identify a suitable installation spread working on construction at a windfarm in the region
design the foundation around the installation spread, this could involve designing the
following parameters accordingly, for example:
o monopile dimensions
o sea-fastening design
The implied objective is to minimise mobilisation and demobilisation costs. Note that the mast
installation will require bespoke mobilisation and foundation installation cranes would normally
require relatively low hook heights, however installation methods are available that avoid
requirements for crane heights to exceed the met mast height.
Hence although attractive and significant cost savings may be achievable, the fundamental
disadvantage due to the high cost of this concept compared with the alternatives presented
below, will remain.
The programme presented in Figure 6 assumes a shorter measurement campaign of three
years due to the need for geotechnical campaign and procurement and construction. Figure 7
indicates that uncertainty is reduced compared with previously examined options.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 9
10 - 13 March 2014
Figure 6: Programme - New Conventional Met Mast
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 7: Evolution of Wind Resource Uncertainty - New Conventional Met Mast
2.4 LiDAR Unit on Lightweight Jacket (LiGA)
LiDAR units impose minimal loading on a foundation structure, allowing lighter-weight
foundation designs to be deployed. A particularly attractive option appears to be a jacket on a
suction-caisson foundation, Figure 8, effectively a derivative of the foundation successfully
deployed at Horns Rev II in 2009.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 10
10 - 13 March 2014
Figure 8: LiGA: LiDAR Unit on Lightweight Jacket
Table 5 presents the key assumptions used for this scenario.
Table 5: LiDAR Unit on Lightweight Jacket (LiGA) - Key Assumptions for Evaluation
Assumption Value Comment
Horizontal Uncertainty 2.0%
Cost High anticipated
Timing 2 years Requires geotechnical survey
The programme would be identical for a conventional met mast, Figure 6, due to a similar need
for geotechnical survey and procurement and assumes three years of measurements at FID.
Figure 9 presents the gradual reduction in the uncertainty in the energy yield of the windfarm.
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 9: Evolution of Wind Resource Uncertainty - LiDAR Unit on Lightweight Jacket
(LiGA)
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 11
10 - 13 March 2014
The value of the campaign could be further increased by also installing a scanning LiDAR on
the structure, thus reducing the horizontal uncertainty across the windfarm, as per Table 6.
Table 6: LiDAR Unit on Lightweight Jacket (LiGA) augmented by Scanning LiDAR unit -
Key Assumptions for Evaluation
Assumption Value Comment
Horizontal Uncertainty 1.0% Measures only radial component of wind vector
hence some uncertainty remains
Additional Cost Medium Costs to be confirmed by commercial
negotiations
Timing No change Requires geotechnical survey
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 10: Evolution of Wind Resource Uncertainty - LiDAR Unit on Lightweight Jacket
(LiGA) with Scanning LiDAR
2.5 Floating LiDAR
LiDAR units on a floating buoy will offer a number of very important practical and economic
advantages once reliable performance has been demonstrated and the wider industry, in
particular Technical Advisers to the investors and banks, feel comfortable. Table 7 presents the
key assumptions used for this scenario.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 12
10 - 13 March 2014
Table 7: Floating LiDAR - Key Assumptions for Evaluation
Assumption
Value
Comment
Horizontal Uncertainty 1.5% Assume buoy is redeployed within the site, thus
providing knowledge of variation of windspeeds
across the site
Cost Medium anticipated
Timing < 1 year
As presented in Figure 11, deployment within a year is possible in theory and taking balanced
view of uncertainties introduced by floater motion, Figure 12 indicates a potentially strong wind
resource estimate at FID.
Figure 11: Programme - Floating LiDAR
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 12: Evolution of Wind Resource Uncertainty - Floating LiDAR
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 13
10 - 13 March 2014
2.6 Shoreline Scanning LiDAR
A shoreline scanning LiDAR campaign could be an attractive option, however there are
relatively few offshore windfarm sites under development where current LiDAR units have
sufficient range. Table 8 presents the key assumptions used for this scenario. Subject to
suitable progress, conclusions could also apply to scanning radar.
Table 8: Shoreline Scanning LiDAR - Key Assumptions for Evaluation
Assumption
Value
Comment
Horizontal Uncertainty 0.0% Assumes twin units and full coverage of the
offshore windfarm site
Cost Medium
Timing < 1 year
Figure 13: Programme - Shoreline Scanning LiDAR
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 14
10 - 13 March 2014
10y P90-EY DCR FID = 10 year, P90 Energy yield estimate, Debt Cover Ratio set at FID
LTR = Long-term reference (wind measurement)
Figure 14: Evolution of Wind Resource Uncertainty - Shoreline Scanning LiDAR
3. Sensitivity Studies
A full three year campaign delivers greatest value; if the campaign is delayed, the value to the
project reduces; however even one year of measurements is worthwhile, as illustrated in Figure
15.
Figure 15: Impact of Delays to Commencement of Measurement Campaign
The main part of the analysis is based on the assumption that annual mean windspeeds vary
from year to year with a standard deviation of 6%. There is some evidence that windspeeds
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 15
10 - 13 March 2014
may be more consistent offshore with reference [3] suggested a figure of 4.2%. Figure 16
examines the sensitivity of the value of wind measurements to this assumption, which show that
the benefits of wind measurements remain substantially unaltered, indeed with a small increase.
sensitivity study with assumption of 4.2% [3]; the equivalent for a reference assumption of 6% is presented in Figure 1
Figure 16: Sensitivity to Annual Average Windspeed Variability
4. Portfolio Benefits
Wind measurements at a particular project can also deliver value to the broader project
development portfolio, in terms of prioritising the projects with the greatest potential, where
capital or construction capability is constrained.
Consider a scenario where five out of ten 700MW projects can be built and a high-quality wind
measurement campaign for Project 1 is deployed, where previously no measurements had
been present (i.e. wind assessment would rely on a wind atlas).
In brief, the analysis methodology used is:
Simulate ten projects, i.e. their actual value;
Estimate the value of these projects perceived without a wind measurement campaign at
Project 1 (Wind Atlas scenario in Table 9); for the purposes of this analysis, the error of this
estimate is determined solely by the uncertainty in the wind measurement;
Select the five best projects as predicted by the estimate value and calculate the true value
of the portfolio (i.e. based on the actual value);
Improve the estimation by implementing a high-quality wind measurement campaign thus
reducing the wind measurement uncertainty, (High Quality Wind Knowledge scenario in
Table 9); reselect the five best projects with this improved knowledge and determine how
much the portfolio increases in value due to this better decision making (note that in many
cases there will be no change).
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 16
10 - 13 March 2014
Table 9: Portfolio Wind Measurement Strategies - Uncertainty Summary
Source of Uncertainty Uncertainty impact on
Wind Knowledge Class
Atlas Low
Quality
High
Quality
Wind
Wind
7.50%
5.48%
4.24%
Energy production
11.25%
8.22%
6.36%
Energy-production component
§
7.23%
Total Energy Uncertainty 13.37% 10.95% 9.63%
§ = See Table 10 for commentary on Technology Maturity
Within the example case presented in Figure 17, the resulting additional knowledge of the wind
resource at Project 1 brings the estimated energy production at Project 1 closer to the actual
value and allows that higher value Project 1 to be selected over Project 8.
On average, this improved decision making will increase the value of the portfolio by around
€10m.
Projects are either “Selected” for construction, or “Abandoned”
Figure 17: Investment Decision for Offshore Windfarm Project Portfolio
5. Discussion and Conclusions
In the current market, the exceedingly high costs for conventional (monopile) offshore met
masts make justifying on-site wind measurements challenging. However measurement
campaigns can indeed deliver considerable value, in terms of reduced uncertainty; this delivers
realisable NPV benefits, for example as improved project finance at FID.
EWEA Windenergy Conference
Wind measurements campaigns offshore -
how they create value for windfarms
Barcelona, Spain
Page 17
10 - 13 March 2014
Much attention is currently being focused on floating LiDAR in particular and this assessment
quantifies the attraction of such a Wind Measurement Strategy.
LiDARs on Light-weight Jacket Structures also appear promising with the advantage of a lower
technical risk.
If present, a nearby met mast is also likely to deliver significant value; indeed its more lengthy
dataset may well compensate for the higher horizontal uncertainty.
In addition to considering the cost-benefit financial analysis of the candidate wind measurement
strategies presented above, the technology maturity of the technology must be taken into
account. Table 10 presents the classes used in the main conclusions presented in Figure 1.
Table 10: Technology Maturity
Technology Maturity
Status
Not Suitable Inherent unsuitable and no prospects of change to status
Low Suitable for some early stage purposes but not currently anticipated to
reach wide-scale acceptance across the offshore wind industry
imminently
Potential
Credible evidence that technology may become fully mature in
timescale of projects currently under development; technology may
already be suitable for early stage assessments and internal decision
making
High Fully mature technology; suitable subject to correct design and
successful deployment and operation
References
1. Matt Taylor, Green Giraffe Energy Bankers; What Do Developers Need To Do To Their Risk
Allocation & Procurement Arrangements To Secure Project Finance?; Wind Power Forums:
Offshore Wind Financial Risk Management Focus Day, London, 14 March 2013
2. Joe Phillips / NORSEWInD; A new wind resource map for the North Sea - Combining the
strengths of Earth Observation data, Mesoscale Modelling and Mast Measurements;
European Offshore Wind, Stockholm; 14 September 2009
http://proceedings.ewea.org/offshore2009/.../131_EOW2009presentation.ppt
3. Berge Erik et al; NORSEWIND Mesoscale model derived Wind Atlases for the Irish Sea,
the North Sea and the Baltic Sea;
http://orbit.dtu.dk/fedora/objects/orbit:119800/datastreams/file_91c79584-33a7-43dd-be61-b277048a274f/content
ResearchGate has not been able to resolve any citations for this publication.
Green Giraffe Energy Bankers; What Do Developers Need To Do To Their Risk Allocation & Procurement Arrangements To Secure Project Finance?; Wind Power Forums: Offshore Wind Financial Risk Management Focus Day
  • Matt Taylor
Matt Taylor, Green Giraffe Energy Bankers; What Do Developers Need To Do To Their Risk Allocation & Procurement Arrangements To Secure Project Finance?; Wind Power Forums: Offshore Wind Financial Risk Management Focus Day, London, 14 March 2013
NORSEWIND – Mesoscale model derived Wind Atlases for the Irish Sea, the North Sea and the Baltic Sea
  • Berge Erik
Berge Erik et al; NORSEWIND – Mesoscale model derived Wind Atlases for the Irish Sea, the North Sea and the Baltic Sea; http://orbit.dtu.dk/fedora/objects/orbit:119800/datastreams/file_91c79584-33a7-43dd-be61-b277048a274f/content