This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, d...

wind speed is one of the major parameters required for an estimation of evapotranspiration and determination of crop water requirements. hence, several models and methods have been developed for a prediction of this needed climatic variable. in recent years, by development of soft computing tools, such intelligent systems as artificial neural network (ann) approach have been widely employed in ...

The appropriate weather prediction is a challenging task and it can be feasible with proper wind speed fluctuation analysis. In this current paper daubechies-4 wavelet is used to analyze the winter wind speed fluctuations due to lesser agitated wind data samples of winter. In summer abrupt changes in wind speed occurs which creates difficulty for wavelets to keep proper track of wind speed fluc...

Wind power generation is characterized by its variability and uncertainty in the wind speed. Due to the irregular nature of wind power production, accurate prediction of wind speed is essential for its application in optimum power flow, transmission congestion, economic load dispatch and electricity market clearing prices. Wind speed of a wind farm is affected by conditions of the environment i...

in this research paper, a 10 minute period measured wind speed data at 10 m, 30 m, and 40 m heights are presented for one of the major provinces of iran. four stations in khuzestan- abadan, hosseyneh, mahshahr, and shushtar- are analyzed to determine the potential of wind power generation in this province. from the primary evaluation and by determining mean wind speed and also the weibull funct...

A method for prediction of wind speed at a selected location based on the data collected at neighborhood locations is presented. The affinity of wind speeds measured at different locations is defined by Pearson’s correlation coefficient. Five turbines with similar wind conditions are selected among 30 wind turbines for in-depth analysis. The wind data from these turbines are used to predict win...

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model predicts wind speed as a set of possible values, which is different from classical time series model...

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 ...

In order to improve the safety of train operation, a short-term wind speed forecasting method is proposed based on a linear recursive autoregressive integrated moving average (ARIMA) algorithm and a non-linear recursive generalized autoregressive conditionally heteroscedastic (GARCH) algorithm (ARIMA-GARCH). Firstly, the non-stationarity embedded in the original wind speed data is pre-processed...