1. The Path to Risk Reduction
Matthew Hendrickson
Sr. Director of Energy Assessment

2. Risk lifecycle through project stages
Generic Project
Risk Relationships
B
Met towers Spatial uncertainty
D A
Time Temporal
uncertainty
C
Generation data Modeling
uncertainty
Turbines Met Towers
Development Operations
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.

3. Year 0: Prospecting stage
Generic Project
Met Tower Years of Data
B
A 0
D A
B 0
C C 0
D 0
Turbines
“High hopes?” “Where to put that first met?”
This stage represents the decision to proceed. It is Uncertainty % Energy
probably the result of a prospecting effort. Measure/temporal n/a
Production estimates formed only from experience and Spatial 27.0%
spatial maps. Model 6.7%
Total 27.8%

4. 6 months: Early decisions
Generic Project
Met Tower Years of Data
B
A 0
D A
B 0
C C 0.5
D 0
Turbines Met Towers
“More mets?” “Expand our position?”
Early on, decisions must be made about how quickly Uncertainty % Energy
and where to expand. Significant investing in land Measure/temporal 9.9%
might be the next stage.
Spatial 8.5%
First few months of data are better than nothing, but still Model 6.7%
not that great.
Total 14.7%

5. Year 2: Time to start marketing
Generic Project
Met Tower Years of Data
B
A 0
D A
B 1
C C 2
D 0.5
Turbines Met Towers
“What’s my price?” “How risky is this?”
After several years, serious marketing is in the works. Uncertainty % Energy
With several years of data on several towers, Measure/temporal 3.9%
uncertainty can reach single digits. Spatial 4.7%
Model 6.7%
Total 9.1%

6. Year 4: Let’s build it
Generic Project
Met Tower Years of Data
B
A 1
D A
B 3
C C 4
D 2.5
Turbines Met Towers
“Did we get enough data?” “nervous”
After four years, the very significant Investment Uncertainty % Energy
Decision is made. It would be nice to have more time Measure/temporal 2.4%
& data, but the market doesn’t always wait.
Spatial 3.8%
With fours years of data on four towers, uncertainty is Model 6.7%
still dropping, but not as fast.
Total 8.1%

7. Year 5 (Ops year 1): First year review
Generic Project
Turbines
“How’d we do?”
With one year of operations, data includes uncertain Uncertainty % Energy
ramp up period. All eyes are on investment Measure/temporal 6.3%
performance.
Spatial 0%
A single year of generation is better than anything that Model 0%
has gone before, but there is pretty high temporal risk.
Total 6.3%

8. Year 6 (Ops year 2): Reforecasting
Generic Project
Turbines
“Time to update budgets?”
After two years, generation expectations are stabilizing Uncertainty % Energy
long term budgets can be revisited. Measure/temporal 3.2%
From here on out, there is only small movements in long Spatial 0%
term expectations, provided there is a decent long term Model 0%
reference.
Total 3.2%

9. 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.

10. 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.

11. 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.

12. 3TIER can help you get to 7%
» Questions?