in recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. for solving this problem, some approaches have been presented. recently, the artificial neural networks (ann) as a heuristic method has more applications for this propose. in this paper, short-term (1 hour) and mid-term (24...

according to this fact that wind is now a part of global energy portfolio and due to unreliable and discontinuous production of wind energy; prediction of wind power value is proposed as a main necessity. in recent years, various methods have been proposed for wind power prediction. in this paper the prediction structure involves feature selection and use of artificial neural network (ann). in ...

With the expansion of wind farm installations in most countries all over the world, the power generation has already significantly influenced on the stability and security of the power grid after gridconnection. Wind power forecasting is an effective method for guarantees stability of the power output from wind farm. This paper proposed an improved GM(1,1) based prediction method, and focuses o...

Numerous studies on wind power forecasting show that random errors found in the prediction results cause uncertainty in wind power prediction and cannot be solved effectively using conventional point prediction methods. In contrast, interval prediction is gaining increasing attention as an effective approach as it can describe the uncertainty of wind power. A wind power interval forecasting app...

This report describes investigations performed for the prediction of the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction is derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave Desert. In addition to a model for power predictio...

This report describes investigations performed for the prediction of the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction is derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave Desert. In addition to a model for power predictio...

The fluctuation of active power output of wind farm has many negative impacts on large-scale wind power integration into power grid. In this paper, flywheel energy storage system (FESS) was connected to AC side of the doubly-fed induction generator (DFIG) wind farm to realize smooth control of wind power output. Based on improved wind power prediction algorithm and wind speed-power curve modeli...

Short-term wind prediction over different time steps is vital for wind farms in operation for various applications. Considering the complexity of atmospheric processes governing wind, time series models are preferred over physical models for wind prediction. Artificial neural networks (ANNs), which perform a non-linear mapping between inputs and outputs, provide an alternative approach for wind...

Due to notable depletion of fuel, non-conventional energy aids the present grid for Power management across the country. Wind energy indeed has major contribution next to solar. Prediction of wind power is essential to integrate wind farms into the grid. Due to intermittency and variability of wind power, forecasting of wind behavior becomes intricate. Wind speed forecasting tools can resolve t...