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摘要:
The impacts of outlying shocks on wind power time series are explored by considering the outlier effect in the volatility of wind power time series. A novel short term wind power forecasting method based on outlier smooth transition autoregressive(OSTAR) structure is advanced, then, combined with the generalized autoregressive conditional heteroskedasticity(GARCH) model, the OSTAR-GARCH model is proposed for wind power forecasting. The proposed model is further generalized to be with fat-tail distribution.Consequently, the mechanisms of regimes against different magnitude of shocks are investigated owing to the outlier effect parameters in the proposed models. Furthermore, the outlier effect is depicted by news impact curve(NIC) and a novel proposed regime switching index(RSI). Case studies based on practical data validate the feasibility of the proposed wind power forecasting method. From the forecast performance comparison of the OSTAR-GARCH models, the OSTAR-GARCH model with fat-tail distribution proves to be promising for wind power forecasting.
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篇名 Wind power forecasting based on outlier smooth transition autoregressive GARCH model
来源期刊 现代电力系统与清洁能源学报(英文) 学科 工学
关键词 OSTAR-GARCH model REGIME SWITCHING index(RSI) OUTLIER effect Wind power forecasting
年,卷(期) 2018,(3) 所属期刊栏目
研究方向 页码范围 532-539
页数 8页 分类号 TM614
字数 语种
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研究主题发展历程
节点文献
OSTAR-GARCH
model
REGIME
SWITCHING
index(RSI)
OUTLIER
effect
Wind
power
forecasting
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研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
现代电力系统与清洁能源学报(英文)
双月刊
2196-5625
32-1884/TK
No. 19 Chengxin Aven
出版文献量(篇)
386
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0
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0
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