Utilization ofwind power as one of renewable resources of energy has been growing quickly all over the world in the last decades. Wind power generation is significantly vacillating due to the wind speed alteration. Therefore, assessment of the output power of this type of generators is always associated with some uncertainties. A precise wind power prediction can efficiently uphold transmission...

The large-scale integration of wind generation imposes several difficulties in the management of power systems. Wind power forecasting up to a few days ahead contributes to a secure and economic power system operation. Prediction models of today are mainly focused on spot or probabilistic predictions of wind power. However, in many applications, endusers require additional tools for the on-line...

The prediction of wind farm output power is considered as an emphatic way to increase the wind energy capacity and improve the safety and economy of the power system. The wind farm output energy depends upon various factors such as wind speed, temperature, etc. , which is difficult to be described by some mathematical expression. This paper introduces a method of wind energy prediction for a wi...

Recent developments in wind energy research including wind speed prediction, wind turbine control, operations of hybrid power systems, as well as condition monitoring and fault detection are surveyed. Approaches based on statistics, physics, and data mining for wind speed prediction at different time scales are reviewed. Comparative analysis of prediction results reported in the literature is p...

Wind power energy has received the biggest attention among the new renewable energies. For achieving a stable power generation from wind energy, the accurate analysis and forecasting of wind power pattern is required. In this paper, we propose subspace clustering method for generating clusters of similar wind power patterns from data to be analyzed and the calendar–based temporal associative cl...

The growing trend of wind generation in power systems and its uncertain nature have recently highlighted the importance of wind power prediction. In this paper a new wind power prediction approach is proposed which includes an improved version of Kriging Interpolation Method (KIM), Empirical Mode Decomposition (EMD), an information-theoretic feature selection method, and a closed-loop forecasti...

Better predictionmodels for the upcoming supply of renewable energy are important to decrease the need of controlling energy provided by conventional power plants. Especially for successful power grid integration of the highly volatile wind power production, a reliable forecast is crucial. In this chapter, we focus on shortterm wind power prediction and employ data from the National Renewable E...

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...

Wind power prediction is one of the most significant technologies to promote the capability of the whole power system that takes in wind electricity. A combined model for wind power forecasting is presented to decrease the influence of reconstructed parameters by chaotic time series analysis and the neural networks (NNs) in this work. The combined model respectively makes use of linear weighted...