The ability to predict wind is crucial for both energy production and weather forecasting. Mechanistic models that form the basis of traditional forecasting perform poorly near ground. Here we take an alternative data-driven approach based on supervised learning. We analyze massive datasets measured from anemometers located at 10 m height in 32 locations central north-west Italy. train learning...

Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA) auto-regressive integrated moving average with exogenous variables (ARIMA...

Major dependency on fossil energy resources and emission of greenhouse gases are common problems that have a very harmful impact human communities. Thus, the use renewable resources, such as wind power, has become strong alternative to solve this problem. Nevertheless, because intermittence unpredictability energy, an accurate speed forecasting is challenging research subject. This paper addres...

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural net...

Wind energy contribution as a source of energy in electric utility systems around the world is on the increase. One of the major challenges of wind energy generation is its natural intermittency; unpredictability, and uncertainty. In this paper, two and three dimensional visualization profiles were presented for the power coefficient. Further, two and three dimensional profiles for the turbine ...

Accurate short-term wind power forecasting with quantification of the associated uncertainty is crucial for the management of energy systems including wind power generation. On top of the inherent uncertainty in wind speed, it is necessary to account also for the uncertainty in the relationship between wind speed and the corresponding power production, typically described by a power curve whose...