Absfrad-The paper presents an advanced wind forecasting system that uses on-line SCAnA measurements, as well as numerical weather predictions (NWP) as input, to predict the power production of wind park8 48 hours ahead. The prediction system integrates models based on adaptive fuzzy-neural networks configured either for short-term (1-10 hours) or longterm (1-48 hours) forecasting. The paper pre...

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...

Accurate quantification and characterization of a wind energy potential assessment and forecasting is significant to optimal wind farm design, evaluation and scheduling. However, wind energy potential assessment and forecasting remain difficult and challenging research topics at present. Traditional wind energy assessment and forecasting models usually ignore the problem of data pre-processing ...

Due to the oil crisis and the insecurity of nuclear energy, the exploitation of renewable energy has attracted researchers’ attentions recently. In particular, to charge electric power in smart grid cities, it is important to integrate multiple renewable energy sources efficiently. Unlike the existing energy sources, the renewable energy sources such as wind and solar have low availability beca...

The intermittence of the renewable sources due to its unpredictability increases the instability of the actual grid and energy supply. Besides, in a deregulated and competitive framework, producers and consumers require short-term forecasting tools to derive their bidding strategies to the electricity market. This paper proposes a novel hybrid computational tool, based on a combination of evolu...

Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed....

Today, among renewable energy sources, wind is used effectively as a clean and sustainable source in electricity generation. The uncertain nature of sources the smart ability neural network approach to process complex time series inputs have allowed use artificial (ANN) methods prediction In this study, speed power turbines generation were estimated from data using networks. our calculations, r...