Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67534
Title: An overview on wind power forecasting methods
Authors: Chai, S
Xu, Z 
Lai, LL
Wong, KP
Keywords: Probabilistic forecast
Wind power forecast
Point forecast
Interval forecast
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Source: 2015 International Conference on Machine Learning and Cybernetics (ICMLC), No. 1Guangzhou, China, 12-15 July 2015, p.765-770 How to cite?
Abstract: With the continually increasing growth in wind generation being integrated into the electric networks, it brings about significant challenges for decision-makers of power system operation due to its high volatility and uncertainty. One efficient approach to tackling such a problem is using reliable forecasting tools. As the conventional point forecasting can only provide a deterministic predicted value, instead, the probabilistic interval forecasting was attracted broad attention in the last few years since it can reflect the information of the uncertainties associated with wind power generation, which can significantly facilitate a large number of decision-making problems in power system operation. This paper presents an overview of current methods used in wind power forecasting. First of all, the frequently-used traditional point forecasting methods are reviewed Afterwards, various state-of-the-art techniques in terms of probabilistic forecasting are discussed. The indications for future development in wind power forecasting approaches and conclusions are given in the end.
URI: http://hdl.handle.net/10397/67534
ISBN: 978-1-4673-7221-3 (electronic)
978-1-4673-7220-6 (CD-ROM)
DOI: 10.1109/ICMLC.2015.7340651
Appears in Collections:Conference Paper

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