Adaptive support segment based short-term wind speed forecasting
Xuguang Wang,
Huan Ren,
Junhai Zhai,
Hongjie Xing and
Jie Su
Energy, 2022, vol. 249, issue C
Abstract:
Accurate wind speed forecasting plays a crucial role in the efficient use of wind energy. This is, however a challenging task due to the volatile and the random nature of the wind speed. To improve the accuracy of wind speed forecasting, we propose the adaptive support segment to characterize the time-varying nature of the wind speed and the inertial property of the airflow. We then propose a hybrid model for wind speed forecasting. In this model, the historical wind speed data is decomposed into narrowband modes using the Variant Mode Decomposition (VMD) method, the adaptive support segment is then estimated and the future measurements for the narrowband modes are forecasted using a modified Reformer model, and the future measurements are finally added together to rebuild the future wind speed. The efficiency of the proposed model is validated through comparative experiments on the wind speed data measured at two wind farms.
Keywords: Adaptive support segment; Wind speed forecasting; Mode decomposition; Reformer; Attention mechanism (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544222005473
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:249:y:2022:i:c:s0360544222005473
DOI: 10.1016/j.energy.2022.123644
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().