NDLI: Short-Term Wind Power Ensemble Prediction Based on Gaussian Processes and Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Duehee Lee Baldick, R.
Copyright Year	2010
Abstract	We propose an ensemble short-term wind power forecasting model that is based on our novel approaches and advanced forecasting techniques in the modern literature. The performance of our model has been verified by forecasting wind power up to 48 hours ahead at seven wind farms for one and a half years. Our model ranked fourth in the Power and Energy Society (PES) wind power forecasting competition. The forecasting model uses 52 Neural Network (NN) sub-models and five Gaussian Process (GP) sub-models in parallel. For 48 hours, the NN sub-models forecast the future wind power based on historical wind power data and forecasted wind information. In parallel, for the first five hours, five GP sub-models are used to forecast wind power using only historical wind power in order to provide accurate wind power forecasts to NN sub-models. These models provide various forecasts for the same hour, so the optimal forecast should be decided from overlapped forecasts by the decision process.
Starting Page	501
Ending Page	510
Page Count	10
File Size	1382589
File Format	PDF
ISSN	19493053
Volume Number	5
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wind forecasting Wind power generation Predictive models Wind speed Forecasting Artificial neural networks Data models wind power forecasting competition Ensemble forecasting Gaussian process neural network
Content Type	Text
Resource Type	Article
Subject	Computer Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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