Extreme Winds -a practical view

Wiebke Langreder1

Jørgen Højstrup1

Lasse Svenningsen2

1 Suzlon Energy A/S, Denmark2 EMD A/S, Denmark

Contents

• The task: Mission Impossible?• What we have done so far• Our results and recommendations so far• What is new• Any ideas?

The task: Mission Impossible?

• Predict maximum 10-minute average windspeed in 50 years.

• Normal situation: 1-5 years of data• Extreme winds are not related to mean

wind speed.

The task: Mission Impossible?

As manufacturer we HAVE to estimate theextreme wind - there is no way around!

How bad is it?

Objective: Choose method to– Minimize bias– Minimize uncertainty

Contents

• The task: Mission Impossible?• What we have done so far• Our results and recommendations so far• What is new• Any ideas?

Establish MethodLong-time series are split in shorter sub-sets,each method is applied to each sub-set.

LT

Sub-set 1 → Vref

Sub-set 2 → Vref

Sub-set 3 → Vref

Sub-set 4 → Vref

Sub-set 5 → Vref

”True” Reference Value

AssumptionThe “true” Vref is determined:• using full data set• extracting Annual Maxima (Periodical

Maxima)• Gumbel distribution

MethodNormalisation with this ”true” value

N subsets → N results per method→ Bias→ Standard deviation

PM: LT → ”True” Vref

Sub-set 1 → Vref

Sub-set 2 → Vref

Sub-set 3 → Vref

Sub-set 4 → Vref

Sub-set 5 → Vref

Method

• Effect of measurement period:Length of sub-sets: 1, 2, 3 and 5 years

Statistical relevance

15 sites (Europe, US, Asia, Roaring 40th)– 158 1 year periods– 77 2 year periods– 49 3 year periods– 22 5 year periods

Previous Methods

• EWTS European Wind Turbine Standard(different variants)

• Gumbel (different variants)

Gumbel? To be or not to be• Parameter describing Gumbel distribution

are determined graphically

Gumbel? To be or not to bePossible reasons for non-linearity:• Wrong way to extract extreme events?• Wrong way to plot/fit?• No convergence towards Gumbel?

Gumbel? To be or not to be

• Different methods to extract extremeevents entering the distribution

• Different plotting positions• Improve convergence with ”pre-

conditioning”

Pre-Conditioning - Improved convergence

• Samples extracted from Weibull parent notnecessarily exponential

• Slow convergence towards Gumbel(exponential)

• Pre-conditioning• Substitution of V with Vc

High end of Vc → exponentialGumbel → exponentialTatata: faster convergence

Contents

• The task: Mission Impossible?• What we have done so far• Our results and recommendations so far• What is new• Any ideas?

Results Gumbel – Bias

Method Bias

Periodical Maximum (PM) +6%

Peak-over-threshold (POT) -5%

Improved method ofindependent storms (IMIS)

-1%

Results Gumbel - Uncertainty

But no matter what Std dev >10%

Method Effect on std devLonger time-seriesFor example 5 yearsinstead of 1 year

-50%

Pre-conditioning -20%

Choice of method +/- 0%

Recommendation

• POT pre-conditioned with factor 2(= dynamic pressure)

Particularly for short time series:• Combine it with EWTS (choose sector with

highest wind speeds)

Contents

• The task: Mission Impossible?• What we have done so far• Our results and recommendations so far• What is new• Any ideas?

Oh dear (1)High correlation between highest measuredwind speed and Vref

Oh dear (2)

Correlation (R2>90%) can be found for• All sites• All methods• Independent of period (1, 2, and 3 years)

Conclusion

• Forget about ”fine-tuning” using differentplotting positions etc.

The main problem is a different one:• Dependency of result from highest event

in sample

If in doubt: Average?

• If N years of data, better results whenaveraging N 1 year Vref?

• No

Any ideas?

Acknowledgement

Thanks to• www.winddata.com• www.undeerc.org/wind• www.bom.gov.au/inside/cgbaps• Risø• Sund & Bælt Holding A/S