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The odor/gas dispersion in atmospheric boundary layer is dominated by airflow. The analysis of the wind speed/direction properties is helpful for understanding the mechanism of odor/gas dispersion. In this paper, twenty groups of wind speed/direction time series are collected using ultrasonic anemometer. The wind speed statistics (including variance, turbulent intensity, skewness, kurtosis and turbulent...
For the variable pitch grid-connected wind turbine maximum power tracking and improved power quality problems, using new double-fed machine constitutes a wind turbine, based on vector control and the whole fuzzy controller is used to achieve brushless doubly-fed variable speed constant frequency motor control. Self correct factor of fuzzy was introduced in the fuzzy controller design process. The...
In order to most effectively utilize the wind energy and improve the efficiency of wind generation system, an optimum control strategy of doublyfed induction generators (DFIG) was proposed, which made the system operation for both the maximum wind enemy captured below the rated wind speed. Based on the wind turbine characteristics and basic electromagnetic relationship of DFIG the mathematical models...
Wind speed forecasting is very important to the utilization of wind energy in wind farm. In order to improve the forecast precision, a forecasting method based on empirical mode decomposition (EMD) and wavelet decomposition combine with least square support vector machine (LSSVM) is proposed in this paper. The wind speed time series was decomposed into several intrinsic mode functions (IMF) and the...
Wind speed and output power forecasting is very important to the utilization of wind energy. In order to improve the forecast precision, a forecasting method based on wavelet transform (WT) and least square support vector machine (LSSVM) is proposed in this paper. The wind speed time series was decomposed into different frequency components. The different LSSVM models to forecast the high frequency...
Wind speed is a kind of non-stationary time series, it is difficult to construct the model for accurate forecast. The way improving accuracy of the model for predicting wind speed up to one-month ahead has been investigated using measured data recorded by wind farm. A forecasting method based on empirical mode decomposition (EMD) and least square support vector machine (LSSVM) is proposed in this...
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