Short-term wind power forecasting with WRF-ARW model and genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Giovanna Martinez-Arellano and Lars Nolle",
  title =        "Short-term wind power forecasting with {WRF-ARW} model
                 and genetic programming",
  booktitle =    "19th International Conference on Soft Computing,
                 MENDEL 2013",
  year =         "2013",
  editor =       "Radomil Matousek",
  address =      "Brno, Czech Republic",
  month =        jun # " 26-28, Brno",
  organisation = "Brno University of Technology",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-80-214-4755-4",
  URL =          "",
  abstract =     "Forecasting wind power in the short-term usually
                 involves the use of numerical weather prediction
                 models. These models need to run at very high
                 resolutions to provide the best forecasts possible.
                 Producing high resolution forecasts is resource and
                 time consuming, which can be a problem when the
                 forecasts need to be available for the grid operator on
                 the day-ahead. This paper introduces a novel approach
                 for short-term wind power prediction by combining the
                 Weather Research and Forecasting - Advanced Research
                 WRF model (WRF ARW) with genetic programming, using the
                 latter one for final downscaling and prediction
                 technique, estimating the total hourly power output on
                 the day ahead at a wind farm located in Galicia,
  notes =        "",

Genetic Programming entries for Giovanna Martinez-Arellano Lars Nolle