NDLI: Numerical analysis of application GARCH to short-term wind power forecasting

Content Provider	IEEE Xplore Digital Library
Author	Hui Zhou Jiangxiao Fang Mei Huang
Copyright Year	2010
Description	Author affiliation: School of Electrical Engineering, Beijing Jiaotong University, China, 100044 (Hui Zhou; Jiangxiao Fang; Mei Huang)
Abstract	For a power grid integrated with wind farms, power output predication of wind turbines would influence the accessibility as well as its economy of dispatch schemes. We applied the GARCH algorithm into construct wind speed model, which has excellent characteristics to tracing the variation of the fluctuated time series. With power curve versus wind speed, wind power is easily gotten by putting the forecasted wind speed into the corresponding equation or curve. Using an example, we verified the validity of forecasting model we proposed. The anticipated wind power would offer dispatch operators a valuable reference. Compared with ARIMA, GARCH demonstrated its advantage in improving prediction accuracy. Using a group of sequences with a variety of volatility clustering to do numerical calculation, the results showed that GARCH has better forecasting performance referred to the sequences which highly fluctuate.
Starting Page	1
Ending Page	6
File Size	666940
Page Count	6
File Format	PDF
ISBN	9781424459384
e-ISBN	9781424459407
DOI	10.1109/POWERCON.2010.5666519
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biological system modeling Indexes Probability Numerical models Turbines Volatility Clustering Wind Speed Forecasting Wind Power Time Series GARCH
Content Type	Text
Resource Type	Article

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