I Workshop Wind GlobalGeo e 3TIER - Matt
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Transcript of I Workshop Wind GlobalGeo e 3TIER - Matt
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The Path to Risk Reduction
Matthew Hendrickson
Sr. Director of Energy Assessment
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Risk lifecycle through project stages
A
B
C
D
Generic Project
Turbines Met Towers
This analysis follows the lifecycle of a project through the
typical development & early operation stages.
Risk associated with long term performance was assessed per
the risk relationships.
Development Operations
Risk Relationships
Met towers Spatial uncertainty
Time Temporal
uncertainty
Generation data Modeling
uncertainty
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Year 0: Prospecting stage
A
B
C
D
Generic Project
Turbines
“High hopes?” “Where to put that first met?”
Met Tower Years of Data
A 0
B 0
C 0
D 0
This stage represents the decision to proceed. It is
probably the result of a prospecting effort.
Production estimates formed only from experience and
spatial maps.
Uncertainty % Energy
Measure/temporal n/a
Spatial 27.0%
Model 6.7%
Total 27.8%
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6 months: Early decisions
A
B
C
D
Generic Project
Turbines Met Towers
Met Tower Years of Data
A 0
B 0
C 0.5
D 0
Uncertainty % Energy
Measure/temporal 9.9%
Spatial 8.5%
Model 6.7%
Total 14.7%
“More mets?” “Expand our position?”
Early on, decisions must be made about how quickly
and where to expand. Significant investing in land
might be the next stage.
First few months of data are better than nothing, but still
not that great.
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Year 2: Time to start marketing
A
B
C
D
Generic Project
Turbines Met Towers
Met Tower Years of Data
A 0
B 1
C 2
D 0.5
Uncertainty % Energy
Measure/temporal 3.9%
Spatial 4.7%
Model 6.7%
Total 9.1%
“What’s my price?” “How risky is this?”
After several years, serious marketing is in the works.
With several years of data on several towers,
uncertainty can reach single digits.
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Year 4: Let’s build it
A
B
C
D
Generic Project
Turbines Met Towers
“Did we get enough data?”
Met Tower Years of Data
A 1
B 3
C 4
D 2.5
Uncertainty % Energy
Measure/temporal 2.4%
Spatial 3.8%
Model 6.7%
Total 8.1%
“nervous”
After four years, the very significant Investment
Decision is made. It would be nice to have more time
& data, but the market doesn’t always wait.
With fours years of data on four towers, uncertainty is
still dropping, but not as fast.
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Year 5 (Ops year 1): First year review
Generic Project
Turbines
“How’d we do?”
Uncertainty % Energy
Measure/temporal 6.3%
Spatial 0%
Model 0%
Total 6.3%
With one year of operations, data includes uncertain
ramp up period. All eyes are on investment
performance.
A single year of generation is better than anything that
has gone before, but there is pretty high temporal risk.
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Year 6 (Ops year 2): Reforecasting
Generic Project
Turbines
“Time to update budgets?”
Uncertainty % Energy
Measure/temporal 3.2%
Spatial 0%
Model 0%
Total 3.2%
After two years, generation expectations are stabilizing
long term budgets can be revisited.
From here on out, there is only small movements in long
term expectations, provided there is a decent long term
reference.
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Best Practices to Reduce Risk
» Collect high quality observations
› Aim for spatial representativeness and height
› Collect at least 1 year at each tower, preferably more
› If met towers don’t extend through plane of rotor, use remote
sensing
› The lack of observations is the biggest risk that people take
» Long Term Referencing
› Without many years from a long term reference, uncertainty is high.
› In most cases, ground based stations are not available. Synthetic
reference are well validated and can reduce uncertainty without
having to collect many years of data. But they are not all equal. Be
a discerning consumer.
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Best Practices to Reduce Risk
» Spatial Modeling
› While models will never replace observations, high quality spatial
models, used with observations, can be a cost effective way of
reducing the number of met towers needed.
» Track risk
› Finally – become diligent at knowing where your risk lies and how
you can better attack it.
› Systematically identify risk in your pipeline and build your energy
assessment program around the systemic reduction of risk.
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In Conclusion – I Propose The Magic 7%
» With many years of Energy Assessment experience, I’ve seen the
best and worst of projects.
» I’ve seen uncertainty estimates of very high quality with many met
towers and tip height sensors - to very low quality with almost no
observations.
» Every program should be designed to resist uncertainty until it
reaches a certain optimal level.
» I propose that 7% energy uncertainty is a target that one should
strive for. It is an achievable level that is still a stretch for some
companies.
» With 7% uncertainty, some simple economic models have a hope
of breaking even during the P95 downside case.
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3TIER can help you get to 7%
» Questions?