Dissertation > Economic > Industrial economy > Industrial economic theory > Industrial sector economy > Electrical and electronics industry > Electricity, motor industry

Short-term Prediction of Wind Speed Based on Wavelet-Autoregressive Integrated Moving Average Model

Author ZhaoXiaoLi
Tutor LvPeng
School North China Electric Power University (Beijing)
Course Applied Mathematics
Keywords Wind speed prediction Rolling time series Wavelet analysis Autoregressive Integrated Moving Average Model
CLC F407.61
Type Master's thesis
Year 2010
Downloads 298
Quotes 2
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Short-term prediction of wind speed is important for utility of wind power. Based on accurate prediction of wind speed, the wind generating plan can be efficiently accommodated to mitigate the impaction from instable wind power on wind grids. The wind speed data from a wind farm measured by 10 minutes is forecasted for short-term based on traditional rolling ARIMA model. On account of non-stationary of the original sequence and outliers, the original data are decomposed and reconstructed by wavelet, then the reconstructed part and the detail part are cumulated to predict the future wind speed, by a comparative anglicizing, the predicting with wavelet-ARIMA model is superior to the traditional rolling one.

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