Page 40 - North American Clean Energy September October 2015

wind power

Avoiding Unpleasant Surprises at the Investment Table

A strategic approach to risk based wind development

by Matthew Hendrickson and Francesca Davidson

Introduction

A common complaint levied against wind projects in the later
development stages is that not enough has been done to shore up
estimates of how much energy the plant will produce. A conident
energy prediction is the result of years of thoughtful planning and

due diligence, and the wind resource assessment program is one
of the most crucial undertakings of the pre-construction phase.
Since the production estimate is usually the most sensitive value
driver in a project pro forma, one wonders why the wind resource

assessment program is so often an afterthought. he primary
reason for this is that the market has not fully appreciated wind
resource assessment risk, mainly because the classic approach to Table 1: Suggested ten-year energy uncertainty levels Figure 2: Forecast of future risk based on impact of proposed
modeling wind resource assessment uncertainty is far too simplis- associated with various stages of investment.
decisions.

tic given the complexities involved, such as, measurement error,
spatial variation, and climate uncertainties. he results can lead
of spatial coverage limits how much gain is possible. So, an uncer- sions, is not the most objective and cost efective approach. Also,
to less trustworthy conclusions with no way to truly diferentiate tainty optimization program is conducted.
without a strong scientiic justiication for the need for expendi-
between the riskiness of several projects. However, with a sophis- he developer examines the impact on calculating uncertainty ture, the wind resource assessment program can sufer from the

ticated risk model in place, it is possible to tailor investment much by adding met towers to the program, allowing each met mast to ever-tightening budget requirements each company faces.
more sensitively to risk. By using future project uncertainty as a collect a year of data – the time remaining until the inal invest- However, with sophisticated risk modeling tools in place, each
barometer, this model allows stakeholders to make decisions to- ment evaluation must be made. Each met tower’s location is investor can make more informed budget decisions using a more
day with the singular goal of balancing current constraints against optimized to ind the locations that have the greatest impact on accurate and systematic approach. Faced with a project which has

a future risk proile preset to the comfort level of the project’s the total, inal uncertainty. With this logic, hundreds of scenarios forecasted uncertainty to be too high at its expected commitment
developer and inanciers.
are modeled, testing each coniguration of met towers. From this date, the developer can choose from the following three choices:
analysis, it is discovered that if two additional met towers are invest appropriately so risk proile and commitment date are met;
Energy risk framework
installed in the next two months, uncertainty will dip below 8.0%, chose to invest less than recommended and push the commitment

It is important to build an articulate model to help manage risk. satisfying internal criteria by the time the investment decision date out; or lower investment standards while keeping the commit-
he framework is actually a collection of models, each one based must be made. he analysis also shows that after a total of three ment date irm. Figure 2. shows a hypothetical budget analysis with
on physical realities which are tied together in a software platform. additional met towers are installed, uncertainty reduction has speciic recommendations for future actions aimed at reducing un-
he uncertainties are allowed to interact with each other through reached the point of diminishing returns. In other words, addi- certainty from a non-investment grade rating of E to an investment

global covariance models. he framework attempts to capture the tional met towers will yield slight gains, but not enough to justify grade of C. Project recommendations are scheduled at dates i-iv.
uncertainty of every step along the way, allowing that uncertainty their upfront capital costs.
to propagate through the entire model to the inal measure of wind Knowledge of how quickly the uncertainty-reduction process Implications

power performance risk. Each uncertainty model is tied to valida- can be sped up by installing equipment and collecting data, ena- Understanding wind project risk is paramount to the ongoing suc-
tion studies or statistical theory, providing a precise rationale for bles stakeholders to understand how much they must invest at cess of this industry. Much underperformance in the industry can be
the structure of the model. A key highlight of this framework is the every stage of project development. he developer also has the linked to poor understanding and management of risk. Next genera-
ability to model future energy-production assessment uncertainty option to accelerate the wind resource assessment program while tion uncertainty models, are required to properly navigate energy

by comparing various scenarios and comparing the outcomes be- minimizing expense.
production risks. Any institution investing in this space should have
fore making investment decisions about the project. For example, a clear idea of its risk proile and equip itself with the tools to ensure
if the developer is choosing between measurement technology Comparing technologies
that its portfolio adheres to a quantiied proile. In wind project
types, such as met towers, sound detection and ranging (SoDAR), his approach is also useful for examining questions about tech- development, time is the resource most often squandered. Typically,

or light detection and ranging (LiDAR), they simply need to test nology choices. For example, what is the diference between there is just one chance to make the best decision. An optimized pro-
the appropriate models created for that technology.
remote sensing technologies? What about the diference between gram is one that uses risk modeling as a regular part of its portfolio
Consider a typical choice made in a wind resource assessment installing an 80-metre met tower or a 100-metre tower? An en- development strategy. When done properly, this helps reduce the
program: determining how much additional meteorological equip- ergy risk framework can be used to develop an investment strat- chances of unpleasant surprises at the investment table.

ment to install at a site. he common way a developer would ap- egy that minimizes required investments while optimizing where
proach this would be with rules of thumb and best practices. Such investment capital is best spent.
Matthew Hendrickson is the manager of energy
rules might include: each project must have a hub height measure- assessment at Vaisala, Inc. (formerly 3TIER).
ment, in simple terrain each project should have at least three met Risk based investment strategy
Mr. Hendrickson has extensive technical

towers per 100MW of installed capacity, and in complex terrain ive A suiciently sensitive risk model enables the process of risk knowledge having personally managed energy
met towers per 100MW. his type of guidance is reasonable, but based wind project investment. Beginning with the end in mind, assessment programs at EDP Renewables,
with a sophisticated uncertainty model, one can do so much better.
each investor should deine its own tolerance for risk. After ob- involving more than 4GW of operating wind farms and
serving numerous uncertainties achieved at the project-invest- a development pipeline of 20GW from 2003 to 2011. He

In Application
ment stage, a rating system may be used as a guide, shown in received his electrical engineering degree from the University
As an example, a developer is managing a 150 MW project in roll- Table 1. Projects are most often inanced at a rating of C or better, of Houston. Vaisala has developed a proprietary model
ing farmland. he project has a single met tower that has collected which is a reasonable target.
called the Energy Risk Framework to measure future project
one year of data. he company needs to have the project ready
With an investment-risk proile, it is possible to begin the task
uncertainty to help clients understand and mitigate wind power

for signiicant investment decisions in the second quarter of the of managing a portfolio of investments on a track that leads each performance risk.
following year. he developer’s investment risk appetite requires project to the desired risk level by the time inal investment com-
that the ten-year energy uncertainty of any project be less than mitments must be made. his usually means the signing of a pow- Francesca Davidson is the energ y communica-
8.0%, in other words, actual energy produced is likely within 8.0% er-purchase agreement or turbine-supply agreement. Along the tions expert at Vaisala, Inc. (formerly 3TIER)

above or below the initial estimate. With just the one met tower, way, each developer should have milestones, attached to uncer- Ms. Davidson is a communications professional
current uncertainty is 11.5%. With limited time and budget, it is tainty levels which correspond to development stages within the and technical writer with 7 years experience
diicult to know the best way to invest to reduce uncertainty to an pipeline. Unfortunately, no company has unlimited resources, and in the renewable energy sector. She received a
Bachelor of Arts degree in English from the University of
acceptable level for inancing. If no additional met tower is added, impacts from current decisions will often only be felt 1 to 2 years
it is expected the uncertainty will drop to just 11.3% by the time into the future. Each investor is forced to balance future risks Washington, where she graduated magna cum laude.
the Q2 investment decisions arises. he model reveals small gains against current budgets. Relying solely on rules of thumb and past
in uncertainty reduction come from additional data, but the lack
experiences, rather than a risk model which can handle these deci-
Vaisala, Inc. | www.vaisala.com

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