The energy industry uses weather forecasts for determining future electricity demand variations due to the impact of weather, e.g., temperature and precipitation. However, as a greater component of electricity generation comes from intermittent renewable sources such as wind and solar, weather forecasting techniques need to now also focus on predicting renewable energy supply, which means adapt...

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements along with model predictions in order to produce a probabilistic wind speed forecast within the pre...

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 ...

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs ...

Wind speed reconstruction is a challenging problem in areas (mainly wind farms) where there are not direct wind measures available. Different approaches have been applied to this reconstruction, such as measure-correlatepredict algorithms, approaches based on physical models such as reanalysis methods, or more recently, indirect measures such as pressure, and its relation to wind speed. This pa...

Wind is the principal driver of the Wind Erosion Prediction System (WEPS), which is a process−based computer model for the simulation of wind−blown sediment loss from a field. WEPS generates wind using a stochastic wind generator. The objectives of this study were to improve the stochastic generation of wind speed and direction and to update the wind statistics used by the generator with statis...

Wind is the principal driver of the Wind Erosion Prediction System (WEPS), which is a process−based computer model for the simulation of wind−blown sediment loss from a field. WEPS generates wind using a stochastic wind generator. The objectives of this study were to improve the stochastic generation of wind speed and direction and to update the wind statistics used by the generator with statis...

An accurate wind speed prediction system is of great importance prerequisite for realizing power grid integration and ensuring the safety system. Quantifying fluctuations can better provide valuable information dispatching. Therefore, this paper proposes a deterministic an interval method based on Lorentzian disturbance sequence. For forecasting, variational modal decomposition algorithm first ...