Forecasts of wind power production are increasingly being used in various management tasks. So far, such forecasts and related uncertainty information have usually been generated individually for a given site of interest (either a wind farm or a group of wind farms), without properly accounting for the spatio-temporal dependencies observed in the wind generation field. However, it is intuitivel...

Probabilistic forecasts account for the uncertainty in the prediction helping the decision makers take optimal decisions. With the emergence of renewable technologies and the uncertainties involved with the power generated through them, probabilistic forecasts can come to the rescue. Wind power is a mature technology and is in place for decades now, various probabilistic forecasting techniques ...

There is an increasing need to forecast power generated by photovoltaic sources in day-ahead power system operation. The electrical energy generated by these renewable sources is an uncertain variable and depends on solar irradiance, which is out of control and depends on climate conditions. The stochastic programming based on various scenarios is an efficient way to deal with such uncertaintie...

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 ...

The prediction of wind direction is a prerequisite for the intelligent and efficient operation of wind turbines. This is a complex task, due to the intermittent behaviour of wind, its non-Gaussian and nonlinear nature, and the coupling between the wind speed and direction. To provide improved wind direction forecasting, we propose a nonlinear model with augmented information from an additional ...