Wind farms are producing a considerable portion of the world renewable energy. Since the output power of any wind farm is highly dependent on the wind speed, the power extracted from a wind park is not always a constant value. In order to have a non-disruptive supply of electricity, it is important to have a good scheduling and forecasting system for the energy output of any wind park. In this ...

Determination of the output power of wind generators is always associated with some uncertainties due to wind speed and other weather parameters variation, and accurate short-term forecasts are essential for their efficient operation. This can efficiently support transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, we ...

Stochastic characteristics of wind power generation may lead to reliability and power quality problems in power systems. This paper presents two control schemes considering state-of-charge (SOC) in the energy storage system for the wind-turbine-generator: constant power mode and power balance mode. Because the response of energy storage system is not fast enough, estimated coming wind power is ...

The wind farm output power have the characteristics of dynamic, random, large capacity etc, which brought great difficulty for incorporating the wind farm in the bulk power system. In order to rationally regulate the power supply system in large grid connected wind power system and reduce the spinning reserve capacity of the power supply system and operating costs, it is necessary to forecastin...

Energy storage is crucial for source-side renewable energy power plants for enhancing output stability and reducing mismatch between power generation and demand. However, installing large size energy storage systems for renewable energy plants may not be economic, due to high capital cost and everincreasing human resources and maintenance cost. As a result, in this paper, a shared energy storag...

Many published studies in wind power forecasting based on Neural Networks have provided performance factors based on error criteria. Based on the standard protocol for forecasting, the published results must provide improvement criteria over the persistence or references models of its same place. Persistence forecasting is the easier way of prediction in time series, but first order Wiener pred...

An accurate forecasting method for power generation of the wind energy conversion system (WECS) is urgently needed under the relevant issues associated with the high penetration of wind power in the electricity system. This paper proposes a hybrid method that combines orthogonal least squares (OLS) algorithm and genetic algorithm (GA) to construct the radial basis function (RBF) neural network ...

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A ...

In this paper, models for shortand long-term prediction of wind farm power are discussed. The models are built using weather forecasting data generated at different time scales and horizons. The maximum forecast length of the short-term prediction model is 12 h, and the maximum forecast length of the long-term prediction model is 84 h. The wind farm power prediction models are built with five d...

Short-term wind speed forecasting is useful for power system to regulate power dispatching plan, decrease reserve power needed and increase the reliability of system. The method of the short-term wind speed prediction is proposed in this paper. The data of wind speed in Dafeng, Jiangsu Province of China is predicted by the model combined with the grey system theory (GST). A grey system model co...