NDLI: Adaptive filtering based short-term wind power prediction with multiple observation points

Content Provider	IEEE Xplore Digital Library
Author	Khalid, M. Savkin, A.V.
Copyright Year	2009
Description	Author affiliation: School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW 2052, Australia (Khalid, M.; Savkin, A.V.)
Abstract	This paper presents a method to improve the short-term wind power prediction at a given turbine using information from numerical weather prediction (NWP) and from multiple observation points which correspond to locations of nearby turbines at a particular wind farm site. The prediction of wind power is achieved in two stages; in the first stage wind speed is predicted using our proposed method. In the second stage, wind speed to output power conversion is accomplished using our proposed power curve (PC) model based on the historical wind speed and power observations at the given wind farm. The proposed wind power prediction method is tested using real measurements and NWP data from one of the wind farm sites in Australia. The performance is compared with the persistence and Grey predictor model in terms of the mean absolute percentage error. The analysis and simulation results demonstrate that the proposed approach gives better performance.
Starting Page	1547
Ending Page	1552
File Size	325799
Page Count	6
File Format	PDF
ISBN	9781424447060
DOI	10.1109/ICCA.2009.5410400
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-09
Publisher Place	New Zealand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptive filters Wind energy Wind farms Wind speed Turbines Weather forecasting Power generation Prediction methods Testing Power measurement wind power Adaptive filtering least squares estimation networked systems prediction
Content Type	Text
Resource Type	Article

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