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

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@InProceedings{Martinez-Arellano:2013:mendel,

• 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 = "https://www.researchgate.net/publication/264397404_Short-term_wind_power_forecasting_with_WRF-ARW_model_and_genetic_programming",
• 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, Spain",
• notes = "http://www.mendel-conference.org/",

}

Genetic Programming entries for Giovanna Martinez-Arellano Lars Nolle

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