Wind 2310
Methods for Wind Resource Characterization

Western Texas College

  1. Course Information
    1. Course Description: In-depth study of regional wind resource assessment, general characteristics of wind resources using statistics and signal processing, resource estimation, and prediction and forecasting.          
    2. Prerequisites:Students must receive a grade of C or better in WIND 1310 to enroll. Students have to be able to read and write on the college level. This class is also math intensive.
    3. Required grade for enrolling in the next course in this sequence:  None
    4. Students must receive a letter grade of a C to be able to enroll in WIND 4323 – Meteorology for Wind Energy and WIND 3310 – Wind Energy Economics and Finances
  2. Student Learning Outcomes:
    1. Students will identify appropriate probability concepts and apply techniques used to solve associated wind energy problems.
    2. Students will develop proper understanding of descriptive and inferential statistical methods and be able to apply them to associated wind energy problems.
    3. Student will acquire a proper understanding of time series analysis and applications to the processing of contextual wind related data.
    4. Students will gain knowledge of basic computational statistical packages and wind specific software used in wind data processing.
  3. Testing Requirements
    1. Campus/Online
      1. The Final exam must be proctored by your professor or an approved testing organization.  (Ask you instructor for more details.)
      2. Students are allowed to use their book and notes while taking their quizzes, Mid-term and Final exam.
      3. Students are allowed to use a calculator on quizzes, Mid-term, and Final exam that are TI-84 and lower.
      4. All quizzes, Mid-terms and Final exams are timed.
  4. Course Requirements
    1. Campus/Online
      1. There will be a mid-term exam.
      2. There will be a comprehensive final exam.
      3. There will one project-based learning activity.
      4. A portion of the students grade is tied to participation and attendance
  5. Information on Books and Other Course Materials
    1. Reference Book:  Daniel S. Wilks, 2006 Statistical Methods in the Atmospheric Science, Academic press, Elsevier, second edition, 603 Pages.
    2. Software: Student will need to be able to download open source software and have Excel.
  6. Grading Breakdown:
    1. Campus /Online

      Homework

      10%

      Quizzes

      10%

      Participation/Discussion

      10%

      Projects

      25%

      Mid-term

      20%

      Final exam

      25%

  7. Other Policies, Procedures and important dates. Please refer to the WTC Catalog for the following
    1. Campus Calendar
    2. Final exam schedule
    3. How to drop a class
    4. Withdrawal information
    5. Student Conduct/Academic Integrity - Students will come to class prepared to participate in the learning process and that part of this preparation will include the demonstration of mature and purposeful behavior. The College Code of Conduct and College Academic Integrity Policies will be followed with no exceptions.
    6. Students with disabilities - As perOP 34.22, any student who, because of a disability, may require special arrangements in order to meet the course requirements should contact the instructor as soon as possible to make any necessary arrangements.  Students should present appropriate verification from Student Disability Services during the instructor’s office hours.  Please note instructors are not allowed to provide classroom accommodations to a student until appropriate verification from Student Disability Services has been provided. 
  8. Course Content
Outline

Unit 1 – Probability and Wind Data Applied Statistics

1.1 Introduction to Signals and their Characterization
1.2 Probabilities
1.3 Conditional Probabilities
1.4 Counting Elements in Sample Space
1.5 Bernoulli Trails – Independent trails with two outcomes
1.6 Markov Chains
1.7/1.8 Random Variables and Distribution
1.9 Moivre- Leplace’s Local and Integral Theorems
1.10 Large Numbers

Unit 2 – Descriptive and Inferential Statistics for Wind Energy

2.1 Introduction to statistics
2.2 Sampling
2.3 Estimation
2.6 Confidence Intervals for Rates

Unit 3 – Wind and Wind Power Time Series

3.1 Time series
3.2 Types of Time Series (Secular, Seasonal, Short, and Random)
3.3 Geostatistics – Parameters of the Weibull Distribution
3.4 Inverse Distance Weighting

Unit 4 – Wind Statistical Prediction

4.1 Scientific Prediction and Linear Models
4.2 Linear Regression Exercises
4.3 Contingency Tables

 

 

 

Last Modified: September 12, 2016