Embedded Files
WEIBULL DISTRIBUTION
The Weibull (why-bull) distribution is used in mechanical life and failure analysis (studying how quickly or how frequently machines fail), and it also has applications in describing wind speed data.
It has two characteristic parameters:
Shape (k)
Larger k value = more spread out
Smaller k value = sharper peak & longer tail
Scale (lambda - 𝝺)
The value at which the distribution reaches its maximum
WEIBULL DISTRIBUTION Example
WEIBULL DISTRIBUTION Example
Watch the video and follow along in the trinket below!
Weibull_Intro.mp4To learn more about Weibull Distributions click this Youtube Video.
Note - This video maker is using different names for lamba & k. (They call them eta & beta).
Step 1 - Run the Weibull Distribution as is shown here.
Step 2 - Alter the lambda to be 100 & record your differences when adjusting lambda.
Step 3 - Change k to be 7, and record the differences that "k" makes to the type of the curve.
Practice Problem
Practice Problem
WIND TURBINE: WEIBULL DISTRIBUTION EXAMPLE
The measured wind speed (m/s) at a proposed wind farm site is described by a Weibull distribution with
k = 2.46 and lambda = 10.5 m/sWind turbines only operate between their ‘cut-in’ speed of 4 m/s and their ‘cut-out’ speed of 25 m/s. They shut down at very high winds to protect themselves from damage.
For an expected year of operation, what percentage of the year do we expect the wind farm to be generating power?
Create a Weibull distribution that helps you determine the percentage of the year the wind farm will generate power.
Expected Output:
Values may be slightly different due to the random number generators.
Wind_Farm_Example_Intro.mp41) Run the code as-is to predict how much of the year a wind farm can generate power when limiting power production between 4 and 25m/s.
2) Record the power production percentage for the year.
3) Alter this code to limit power production to 5-15 m/s.
4) What is the new production percentage?
Page updated
Report abuse