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Short Term Wind Power Prediction Using Wavelet Transform and ARIMA
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作者 In-Yong Seo Bok-Nam Hat +3 位作者 sang-ok kin Won Nam-Koong Dong-Wan Seo Seong-JunKim 《Journal of Energy and Power Engineering》 2012年第11期1786-1790,共5页
A sustainable production of electricity is essential for low carbon green growth in South Korea. Although wind energy is unlimited in potential, both intermittency and volatility should be tackled for smart grid integ... A sustainable production of electricity is essential for low carbon green growth in South Korea. Although wind energy is unlimited in potential, both intermittency and volatility should be tackled for smart grid integration in future. To cope with this, many works have been done for wind speed and power forecasting. It is shown that statistical techniques are useful for short-term forecasting of wind power. This paper presents a statistical wind speed forecasting. The wavelet decomposition is employed as a de-noising technique. An illustration will be given by real-world dataset. According to the result, the MAD (mean absolute deviation) is improved as much as 10%. 展开更多
关键词 Wind speed forecasting autoreressive model wavelet decomnosition mean absolute deviation.
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