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DNV GL © 2014 14 January 2015 SAFER, SMARTER, GREENER DNV GL © 2014
14 January 2015 Taylor Geer
ENERGY
The impact of non-linear effects on preconstruction uncertainty modeling
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DNV GL © 2014 14 January 2015
Overview
What is the Sensitivity Ratio
How can industry common practice be improved
Other non-linearities in uncertainty modeling
What is the impact
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What is the Sensitivity Ratio?
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What is the Sensitivity Ratio?
indicates how sensitive the production is to changes in wind speed
is dependent mainly on the wind speed distribution and power curve of the turbine
For example: with a sensitivity ratio of 1.50, a 2.0% reduction in wind speed at all masts would lead to a 3.0% reduction in net energy production.
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Why is it important
The sensitivity ratio is our tool for converting wind speed uncertainties into energy uncertainties.
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Measurements
Correlations
IAV of Wind Speed
Vertical Extrapolation
Spatial Extrapolation
Loss factors Energy IAV
SR
Net energy distribution/Project Uncertainty
Gross energy distribution
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What is the industry common practice?
Linear relationship determined from a single perturbation value (3%, 1 SD, etc.) to the wind speed input of the energy model
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Δ energy
Δ wind speed
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑅𝑅𝑆𝑆𝑅 = Δ 𝑆𝑆𝑆𝑒𝑒𝑆
Δ𝑤𝑆𝑆𝑤 𝑆𝑠𝑆𝑆𝑤
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How can industry common practice be improved?
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Calculate change in energy at multiple steps over a wider range of wind speeds to develop a “Sensitivity Curve”
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
110.00%
120.00%
130.00%
140.00%
70% 80% 90% 100% 110% 120% 130%
% C
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in A
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En
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% Change in Annual Wind Speed
Lower sensitivity at high wind speeds means upside benefit is muted
Higher sensitivity at lower wind speeds means downside impact is amplified
20 January, 2015 Private and confidential
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Sensitivity Curve – impact on gross distribution
Gross distribution incorporates all wind speed uncertanties, converted to energy.
Obvious skew to distribution resulting from shape of power curve
– Mean gross production <> median (P50) gross production
– Asymmetric uncertainty profile (less upside potential)
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Linear Non-Linear
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Other non-linearities in uncertainty modeling
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System availability variability
Availability variability is significant
Availability variability is not normally distributed
636 project years
165 projects
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Impact on net distribution
Net distribution incorporates all project uncertanties.
Obvious skew to distribution, but more muted that gross distribution
– Mean net production <> median (P50) net production
– Asymmetric uncertainty profile (less upside potential)
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Linear Non-Linear
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What is the impact?
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Impact of Sensitivity Curve on uncertainty analysis
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Parameter Typical range of impact
Gross P50 0.0% to -0.4%
Net P50 0.1% to -0.6%
10-Year P90/P50 0.1% to -0.6%
1-Year P99/P50 0.5% to -4.0%
Only in low sensitivity, high uncertainty projects! Otherwise typically -0.6%
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0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
40.00%
60.00%
80.00%
100.00%
120.00%
140.00%
160.00%
70% 80% 90% 100% 110% 120% 130%
Pro
bab
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of
occ
ura
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% C
han
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in E
ner
gy
% Change in Wind Speed
Why high uncertainty project are impacted more greatly
20 January, 2015 Private and confidential
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Conclusions
Linear model may be under predicting the risk on “low sensitivity ratio” project, which appear to be low risk. Moving to a non-linear uncertainty model will allow for a more realistic representation of production variability and risks. The largest quantitative impact will be on high uncertainty/low sensitivity projects. P50 <> Mean, we’ll need to be more precise in our language.
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SAFER, SMARTER, GREENER
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Questions?
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Taylor Geer [email protected] +1 503 222 5590