Wind Energy Education
2-Year Transfer Curriculum
Sample Course
©
WE 2310
Methods for Wind Resource Characterization
3 Credit Hours
www.texaswindenergyinstitute.ttu.edu
© Texas Tech University 2011
WE 2310
Required Textbook:
No textbook is required other than the lecture notes.
Reference Book:
Title: Statistical Methods in the Atmospheric Sciences
Author: Daniel S. Wilks
Publisher: Academic Press, Elsevier, second edition, 630
pages (2006)
© Texas Tech University 2011
WE 2310
Expected Learning Outcomes:
Upon completion of this course, the student will:
• Have an understanding of the concept of “Probability” through its
various definitions and be able to solve associated wind energy
practical problems
• Possess a proper knowledge about descriptive statistical methods
and be able to apply it to associated wind energy practical problems
• Be familiar with inferential statistical methods and its applications
to contextual wind and wind power data
• Have a proper understanding of time series analysis and how it is
applied to the processing of contextual wind and wind power data
• Be familiar with some computational statistical packages and know
how to use them in wind and wind power data processing
© Texas Tech University 2011
WE 2310
Course Units:
Unit I: Probability and wind data
Unit II: Applied statistics of wind and wind power data
Unit III: Descriptive statistics of wind and wind power data
Unit IV: Inferential statistics of wind and wind power data
Unit V: Wind statistical prediction
Unit VI: Wind and wind power time series
© Texas Tech University 2011
WE 2310
Sample Topic: The Weibull Distribution
• In order to obtain an estimate of the energy production of wind
turbines at a given site, information about wind climatology is
needed.
• Wind-speed time series are used to obtain the statistical description
of wind speed at the site.
• Parameters like mean, mode, median and standard deviation are
very useful as well as the determination of the Probability Density
Function (PDF) and the corresponding Cumulative Distribution
Function (CDF).
• The most common distribution is the normal distribution (Gaussian)
but observational data have shown that “wind-speed” as a variable
does not fit into a normal distribution.
• Usually, for wind-speed data the Weibull Distribution is the proper
one.
© Texas Tech University 2011
WE 2310
Sample Illustrative Slide:
The mathematical definition of the Weibull Distribution
Probability Density Function
Cumulative Distribution Function
The Weibull Distribution is a bi-parametric function (α and β are the parameters
© Texas Tech University 2011
WE 2310
Sample Illustrative Slide:
Weibull Distribution PDF’s for 4 values of α-parameter
© Texas Tech University 2011
WE 2310
Sample Assessment Questions:
1) What is the main visual distinction between the normal and
Weibull distributions?
2) For which values of the α-parameter can the Weibull
Distribution be approximated to a normal one?
3) Explain the distinction between a PDF and its corresponding
CDF
© Texas Tech University 2011