Wind energy production has had accelerated growth in recent years, reaching an annual increase of 17% 2021. speed plays a crucial role the stability required for power grid operation. However, wind intermittency makes accurate forecasting complicated process. Implementing new technologies allowed development hybrid models and techniques, improving accuracy. Additionally, statistical artificial ...

Nonlinear model structure selection (MSS) is an important step in the modeling theory of the nonlinear system. The proper model structure and model parameters estimation can be used to reduce unnecessary computations and improve the model forecast accuracy. This paper mainly investigates the short-term wind speed forecasting (STWSF) by utilizing the comprehensive MSS technique based on real dat...

Generation and load balance is required in the economic scheduling of generating units in the smart grid. Variable energy generations particularly from wind and solar energy resources are witnessing a rapid boost, and, it is anticipated that with a certain level of their penetration, they become noteworthy sources of uncertainty. As in the case of load demand, energy forecasting can also be use...

In this study, an ARX model with nonparametric multi time scale regression model was proposed for short term gust forecasting and applied to a ski resort in Japan. Proposed ARX model can be used for short term forecasting of mean and fluctuating wind speed. Proposed nonparametric multi time scale regression model can appropriately estimate the peak factor and shows better agreement with the mea...

Weather forecasting is crucial to both the demand and supply sides of electricity markets. Temperature has a great effect on energy demand. Moreover, solar and wind are very promising renewable energy sources. In this paper, a large vector autoregression (VAR) model is built to forecast three important weather variables for 61 cities around the United States. We estimate the VAR model with 16 y...

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are base...

The bootstrap resampling method is applied to an ensemble artificial neural network (ANN) approach (which combines machine learning with physical data obtained from a numerical weather prediction model) to provide a multi-ANN model super-ensemble for application to multi-stepahead forecasting of wind speed and of the associated power generated from a wind turbine. A statistical combination of t...

Wind generation is hectic by nature, making wind power forecasting highly challenging, particularly for short time frames. Forecasting of wind power is becoming progressively more important to power system operators and electricity market.Wind power is variable and irregular over various timescales as it is weather dependent. Thus precise forecasting of wind power is acknowledged as a major con...