Summary
In this paper, we propose a method to predict wind power production with radial basis function networks. In this case, the power production is the aggregated production of all wind farms of one electricity company. The method uses wind speed predictions supplied by a meteorological agency, and predicts up to several days ahead. The coarse resolution of one meter per second is overcome by combining the weather data from several meteorological stations. The wind direction is mapped on a circle, so it is more compatible with a radial basis. These ingredients have been combined with a kernel machine, which has been implemented and tested. Test results are presented in the paper.
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Extract
Short-Term Wind Power Prediction with Radial Basis Networks
1. Introduction
The endeavour to reduce the amount of carbon dioxide in the atmosphere [8] has been ongoing for a while. The European Union (EU)'s renewables directive has been in place since 2001 [9] . It aims to raise the share of electricity produced from renewable energy sources (RES) in the EU to 22% by 2010. The efficiency of wind power turbines have been significantly improved during the last decade, and have become an attractive source of renewable energy. At the moment, wind power is the fastest growing type of renewable energy in Europe.However, wind power also has the other side of the coin: because the amount of energy produced strongly depends on the actual wind speed at ...See the full content of this document
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