A Hybrid Wind Speed Forecasting System Based on a ‘Decomposition and Ensemble’ Strategy and Fuzzy Time Series

Hufang Yang, Zaiping Jiang and Haiyan Lu
Additional contact information
Hufang Yang: School of Statistics, Dongbei University of Finance and Economics, Dalian, 116025, China
Zaiping Jiang: School of Statistics, Dongbei University of Finance and Economics, Dalian, 116025, China
Haiyan Lu: Faculty of Engineering and Information Technology, University of Technology, Sydney, 20000, Australia

Energies, 2017, vol. 10, issue 9, 1-30

Abstract: Accurate and stable wind speed forecasting is of critical importance in the wind power industry and has measurable influence on power-system management and the stability of market economics. However, most traditional wind speed forecasting models require a large amount of historical data and face restrictions due to assumptions, such as normality postulates. Additionally, any data volatility leads to increased forecasting instability. Therefore, in this paper, a hybrid forecasting system, which combines the ‘decomposition and ensemble’ strategy and fuzzy time series forecasting algorithm, is proposed that comprises two modules—data pre-processing and forecasting. Moreover, the statistical model, artificial neural network, and Support Vector Regression model are employed to compare with the proposed hybrid system, which is proven to be very effective in forecasting wind speed data affected by noise and instability. The results of these comparisons demonstrate that the hybrid forecasting system can improve the forecasting accuracy and stability significantly, and supervised discretization methods outperform the unsupervised methods for fuzzy time series in most cases.

Keywords: wind speed forecasting; hybrid forecasting system; data pre-processing; fuzzy time series; comprehensive evaluation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/9/1422/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/9/1422/ (text/html)

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:gam:jeners:v:10:y:2017:i:9:p:1422-:d:112222

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager (indexing@mdpi.com).