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Improving Wind Ramp Predictions Using Gabor Filtering And Statistical Scenarios

  • Author / Creator
    Li, Yaqiong
  • The increase of wind penetration into electric power system creates challenges to power grid management due to the variable nature of wind. Unlike conventional power plants, such as thermal, gas or hydro-based plants, wind power generation is not controllable. For example, days of calm weather may suddenly be followed by gusty winds associated with a storm or a front. The current wind power forecasting methodologies, which combine Numerical Weather Prediction (NWP) models and mathematical methods, have been well established during the last decade. However, this forecasting methodology has demonstrated a limited ability to forecast wind ramp events, which are defined as sudden, large changes in wind production. In this study different strategies are developed to improve wind ramp prediction and to provide additional probabilistic information of wind ramp occurrences to end users. First, a methodology of separate wind power predictions based on different weather regimes is presented. Second, an independent wind ramp prediction system is proposed to complement conventional ramp predictions. This system integrates information about the pressure gradient that is extracted by applying Gabor filters to two-dimensional pressure grids. Third, the temporal uncertainty of wind ramp occurrences is addressed using power scenarios generated from quantile forecasts of wind power. The probability of a wind ramp occurrence conditional to the number of scenarios predicting the ramp within certain time intervals is estimated using a logistic regression technique. The proposed strategies were tested on four wind farms located in southern Alberta, Canada, and their performance is discussed.

  • Subjects / Keywords
  • Graduation date
    2014-06
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3F18SP55
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Electrical and Computer Engineering
  • Specialization
    • Software Engineering and Intelligent Systems
  • Supervisor / co-supervisor and their department(s)
    • Lozowski, Edward (Earth and Atmospheric Science)
    • Musilek, Petr (Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Reformat, Marek (Electrical and Computer Engineering)
    • Gomide, Fernando (University of Campinas)
    • Rivard, Benoit (Earth and Atmospheric Science)
    • Pedrycz, Witold (Electrical and Computer Engineering)