The Path to Risk ReductionMatthew HendricksonSr. Director of Energy Assessment
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.
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%
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%
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%
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%
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%
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%
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.
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.
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.