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Integrated Machine Learning and Enhanced Statistical Approach-Based Wind Power Forecasting in Australian Tasmania Wind Farm
Joint Authors
Song, Li
Yao, Fang
Zhao, Xingyong
Liu, Wei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-16
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper develops an integrated machine learning and enhanced statistical approach for wind power interval forecasting.
A time-series wind power forecasting model is formulated as the theoretical basis of our method.
The proposed model takes into account two important characteristics of wind speed: the nonlinearity and the time-changing distribution.
Based on the proposed model, six machine learning regression algorithms are employed to forecast the prediction interval of the wind power output.
The six methods are tested using real wind speed data collected at a wind station in Australia.
For wind speed forecasting, the long short-term memory (LSTM) network algorithm outperforms other five algorithms.
In terms of the prediction interval, the five nonlinear algorithms show superior performances.
The case studies demonstrate that combined with an appropriate nonlinear machine learning regression algorithm, the proposed methodology is effective in wind power interval forecasting.
American Psychological Association (APA)
Yao, Fang& Liu, Wei& Zhao, Xingyong& Song, Li. 2020. Integrated Machine Learning and Enhanced Statistical Approach-Based Wind Power Forecasting in Australian Tasmania Wind Farm. Complexity،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1145485
Modern Language Association (MLA)
Yao, Fang…[et al.]. Integrated Machine Learning and Enhanced Statistical Approach-Based Wind Power Forecasting in Australian Tasmania Wind Farm. Complexity No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1145485
American Medical Association (AMA)
Yao, Fang& Liu, Wei& Zhao, Xingyong& Song, Li. Integrated Machine Learning and Enhanced Statistical Approach-Based Wind Power Forecasting in Australian Tasmania Wind Farm. Complexity. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1145485
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1145485