Extreme wind speed predictions using the Method of Independent ...

Extreme wind speed
predictions using the
Method of Independent Storms
(MIS)
VindKraftNet: Extreme winds meeting at Risø DTU
2 nd September 2009
Bob Hodgetts

What is an MIS analysis
In simple terms, a Gumbel analysis from time series data
Key input:
Seven years of ten-minute or hourly time series data
Basics of the method:
• Identify the maximum wind speeds recorded;
• Ensure each maximum is from an independent storm;
• Conduct a Gumbel analysis of the extreme wind speeds
Result:
A predicted extreme wind speed trend

Indentify independent storms
40
Independent storms (more than 48 hours apart)
35
30
Mean wind speed [m/s]
25
20
15
10
Storm
threshold
5
0
01/01/2009 03/01/2009 05/01/2009 07/01/2009 09/01/2009 11/01/2009 13/01/2009 15/01/2009

Example result
Assumes extreme events are from the same wind mechanism

Typical MIS prediction
• 2 years of on site wind measurements
• Correlate to reference station with 7+ years consistent data
• Predict long-term time series at site mast
• Run a MIS or similar model to predict extreme wind speed,
usually a ten-minute of hourly value
• Analyse site gust ratio to factor ten-minute or hourly
extreme to 3 second gust value
Differences in MCP review compared to energy assessments
Pro: Does the quality of the correlation need to be as good
Con: Need 7+ years of time series data which can be expensive

MIS predictions at turbines
• Extreme wind speeds predicted at masts
• Long-term time series synthesised at turbines from mast
using directional speed-ups determined in wind flow model
• MIS model run for each turbine
• Gust ratios predicted to turbines
(based on assumption of constant standard deviation of wind speed)
Uncertainties will always be significant
• Uncertainty in general MIS method
• Correlation to reference data
• Wind flow model

35%
Indication of uncertainty in MIS
• Seven long-term reference stations considered
• Periods of consistent data from 11 to 20 years
• Each station time series cut-up into lots of shorter periods and run
through MIS prediction
• Results are standard deviations of all results obtained about the
mean result for each station
Standard Deviation of different results
30%
25%
20%
15%
10%
5%
Average line
0%
1 year 2 years 3 years 4 years 5 years 6 years 7 years
Period of data used for prediction

Thank you
Any questions after today then please get in touch:
bob.hodgetts@garradhassan.com