Wind speed forecasting using a portfolio of forecasters

This contribution presents the application of a portfolio of forecasters to the problem of wind speed forecasting. This portfolio is created using a single time series and it is based on a number of time series characteristics, previously proposed, and a set of novel time series features. The results show that the proposed portfolio produces accurate predictions, and, has better performance than the forecasters composing it. In addition to this, the forecast values are used to determine the power generation capacity of a wind turbine driven a permanent magnet synchronous generator. © 2014 Elsevier Ltd.

Algorithm portfolio; Algorithm selection problem; Power generation capacity; Time series forecasting; Wind turbines Forecasting; Genetic algorithms; Permanent magnets; Time series; Time series analysis; Wind turbines; Algorithm portfolios; Algorithm selection; Permanent magnet synchronous generator; Power generation capacities; Time series characteristic; Time series features; Time series forecasting; Wind speed forecasting; Wind; accuracy assessment; algorithm; forecasting method; performance assessment; power generation; time series; wind turbine; wind velocity; renewable resource; time series analysis; weather forecasting

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