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Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
Joint Authors
Niu, Mingfei
Sun, Shaolong
Zhang, Yuanlei
Wu, Jie
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-01
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation.
In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation.
However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult.
This paper proposes a novel combination bias correcting forecasting method, which includes the combination forecasting method and forecasting bias correcting model.
The forecasting result shows that the combination bias correcting forecasting method can more accurately forecast the trend of wind speed and has a good robustness.
American Psychological Association (APA)
Niu, Mingfei& Sun, Shaolong& Wu, Jie& Zhang, Yuanlei. 2015. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073577
Modern Language Association (MLA)
Niu, Mingfei…[et al.]. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1073577
American Medical Association (AMA)
Niu, Mingfei& Sun, Shaolong& Wu, Jie& Zhang, Yuanlei. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073577
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073577