in this paper, a new approach is proposed in order to select an optimal membership function for inputs of wind speed prediction system. then using a fuzzy method and the stochastic characteristics of wind speed in the previous year, the wind speed modeling is performed and the wind speed for the future year will be predicted. in this proposed method, the average and the standard deviation of in...

In this paper, a new approach is proposed in order to select an optimal membership function for inputs of wind speed prediction system. Then using a fuzzy method and the stochastic characteristics of wind speed in the previous year, the wind speed modeling is performed and the wind speed for the future year will be predicted. In this proposed method, the average and the standard deviation of in...

Abstract. Wind as a resource of renewable energy has obtained an important share of the energy market already. Therefore simulation and prediction of wind speeds is essential for both, for engineers and energy traders. In this paper we analyze the surface wind speed data from three prototypic locations: coastal region (Rotterdam), undulating forest landscape few 100 m above sea level(Kassel), ...

For accurate and efficient use of wind power, it is important to know the statistical characteristics, availability, diurnal variation, and prediction of wind speed. Prediction of wind power permits the scheduling of the connection or the disconnection of wind turbines to achieve optimal operating costs. In this paper, a simple and accurate method for predicting wind speed based on weather-sens...

Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depend...

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...

This paper presents a hybrid neural network approach to predict wind speed automatically in renewable energy systems. Wind energy is one of the renewable energy systems with lowest cost of production of electricity with largest resources available. By the reason of the fluctuation and volatility in wind, the wind speed prediction provides the challenges in the stability of renewable energy syst...

In wind farms, individual turbines disturb the wind field by generating wakes that influence other turbines in the farm. From a control point of view, there is an interest in dynamic optimization of the balance between fatigue and production, and an understanding of the relationship between turbines manifested through the wind field is hence required. This paper develops models for this relatio...

Wind power prediction accuracy is important for assessing the security and economy when wind power is connected to the grid, and wind speed is the key factor. This article presents a future four hours prediction scheme that combined chaos phase space reconstruction with NWP method. Historical wind speed data are reconstructed as phase space vectors, which are used as the first input part of pre...