POWER January 2015 - 36

RENEWABLE POWER
tion, not wind speed.
Still, according to Taylor, several macro-factors
have increased the attractiveness
of wind hedges. As wind generation
has become a more mature industry, turbine
hardware and development costs have
fallen and become more standardized. At
the same time, project outputs across the
industry have in many cases fallen well below
projections, while some areas have experienced
prolonged, unexpected periods
of low wind volume.
This latter factor has resulted in lenders
taking much more conservative approaches to
project loans, assuming worst-case-scenario
wind volumes. It is not unusual for wind farm
lenders to assume annual wind volumes that
are 30% (or more) below expected levels.
With assumed revenue being so much lower,
access to debt financing is restricted and the
cost of that debt can increase, perhaps to the
point of making the project uneconomic, as
Wells discovered.
Shifting Risk
Of course, a hedge is not just about reducing
one party's costs of financing. It also requires
a second party willing to take on that risk.
And it's there that wind and solar hedging is
still in the early stages.
From one perspective, renewable risk hedging
is attractive to large investors, because it
is not correlated with the performance of the
financial markets and is mean-reverting (in
other words, over time, wind volume will
tend to remain near historical averages). But
while the financial markets have a wide variety
of parties willing take on all sorts of risks,
the opportunities for accessing wind volume
risk are limited because active risk-transfer
markets for it are limited-a party wishing to
offload the risk later may have trouble finding
a buyer. Taylor said that right now, reinsurance
firms and large institutional investors, in
the form of investor-linked-securities funds,
are the main customers.
There are various ways such a hedge can
be constructed. One way in which wind
hedges differ from other hedges in the energy
sector is that longer terms are available, up to
10 years (as is the case for Black Oak). This
is because, in contrast to fuel price hedges,
in which uncertainty increases the further
out one goes, wind volume tends to become
more predictable over longer periods because
weather patterns are expected to revert to the
mean. This makes the risk for wind farm output
more quantifiable.
Hedges can also be structured either as
swaps, where there is a single price point
( " strike " ) determining which party pays
out, or as collars, where there are upper and
lower strikes, in between which neither par36
ty
pays. A study Taylor conducted in 2013
demonstrated that collars tended to produce
the biggest increase in a project's net present
value, though in every case REsurety
considered, hedging wind volume risk produced
an increase.
Given the apparent advantages of hedging
wind volume risk, why hasn't it caught
on yet?
One barrier is that awareness of these
financial instruments appears quite low:
Many project owners may not even be aware
they exist.
Second, because the sector is so new, little
standardization exists in the market, meaning
that solutions must be custom-tailored
for each project. That makes it harder to find
parties willing to take on the risk.
Third, accurate risk assessment for something
as variable and localized as wind farm
output requires highly robust data. Past efforts
at risk trading in wind power typically
foundered on poor data, which made the
products uneconomic for wind developers.
It's there that things may finally be
changing.
Time for Big Data
Obviously, weather-related hedging depends
heavily on predicting the weather, and predicting
the future requires understanding of
past trends. But many of the factors affecting
wind and solar plant performance-such
as solar irradiance and highly localized wind
speeds-haven't been measured to the degree
necessary to make accurate predictions
of output, until relatively recently, which
means the data quality hasn't been good
enough for this sort of risk assessment. And
www.powermag.com
it's also taken advances in computing power
and data mining to make use of the information.
Put another way, the number crunching
simply hasn't been up to the task until the
past couple of years.
Seattle-based 3TIER, a subsidiary of
Finnish company Vaisala, provides weather
forecasts for 130 GW of renewable capacity
worldwide, amounting to more than 900
different projects. It's developed robust
datasets of wind speed and solar irradiance,
but its solar dataset for the U.S., for
example, goes back only about 15 years (its
wind data is more robust, going back about
twice that far).
Still, what it's seen is that even desert locations
during the summer, far from being
continually sun-drenched, in fact experience
considerable variations in year-over-year irradiance.
Its 2014 review of June-to-August
irradiance showed most of the U.S. falling
at least 10% below the 15-year average
(Figure 2).
Of particular note in the 3TIER study
was a focus on the Ivanpah Solar Electric
Generating Station in California (POWER's
2014 Plant of the Year), which has drawn
controversy this summer for falling below its
planned output. The 3TIER study found that
the Ivanpah site experienced direct normal
irradiance 5% to 8% below average in July
and August. Further, the site has experienced
solar irradiance either above or below expectations
in 10 out of 15 summer months over
the past five years.
" The impact of solar variability on the
balance sheet can and will make the difference
between profitability and loss, " Richard
Pyle, Vaisala's energy segment director said.
POWER | January 2015
2. Cloudy record. Solar irradiance levels in the U.S. in summer 2014 were considerably
below average across much of the country, including in normally sunny areas such as Nevada
and California. Courtesy: 3TIER/Vaisala

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POWER January 2015

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