A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting
Joint Authors
Zhang, Wenyu
Qu, Zongxi
Zhang, Wenyu
Leng, Wennan
Wang, Jianzhou
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-08
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
As a type of clean and renewable energy, the superiority of wind power has increasingly captured the world’s attention.
Reliable and precise wind speed prediction is vital for wind power generation systems.
Thus, a more effective and precise prediction model is essentially needed in the field of wind speed forecasting.
Most previous forecasting models could adapt to various wind speed series data; however, these models ignored the importance of the data preprocessing and model parameter optimization.
In view of its importance, a novel hybrid ensemble learning paradigm is proposed.
In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series.
To estimate the forecasting ability of the proposed model, 15 min wind speed data for wind farms in the coastal areas of China was performed to forecast as a case study.
The empirical results show that the proposed hybrid model is superior to some existing traditional forecasting models regarding forecast performance.
American Psychological Association (APA)
Qu, Zongxi& Zhang, Wenyu& Wang, Jianzhou& Zhang, Wenyu& Leng, Wennan. 2016. A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting. Advances in Meteorology،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1095442
Modern Language Association (MLA)
Qu, Zongxi…[et al.]. A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting. Advances in Meteorology No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1095442
American Medical Association (AMA)
Qu, Zongxi& Zhang, Wenyu& Wang, Jianzhou& Zhang, Wenyu& Leng, Wennan. A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting. Advances in Meteorology. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1095442
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1095442