Bibliographic Details
| Title: |
A Novel Hybrid Approach Based on Wavelet Transform and Fuzzy ARTMAP Networks for Predicting Wind Farm Power Production. |
| Authors: |
Haque, Ashraf Ul1, Mandal, Paras2, Meng, Julian3, Srivastava, Anurag K.4, Tseng, Tzu-Liang2, Senjyu, Tomonobu5 |
| Source: |
IEEE Transactions on Industry Applications. Sep2013, Vol. 49 Issue 5, p2253-2261. 9p. |
| Subject Terms: |
*Wind power plants, *Power resources forecasting, *Algorithms, Wavelet transforms, Fuzzy control systems, Soft computing, Scientific communication |
| Abstract: |
This paper presents a novel hybrid intelligent algorithm based on the wavelet transform (WT) and fuzzy ARTMAP (FA) network for forecasting the power output of a wind farm utilizing meteorological information such as wind speed, wind direction, and temperature. The prediction capability of the proposed hybrid WT +FA model is demonstrated by an extensive comparison with a benchmark persistence method, other soft computing models, and hybrid models as well. The test results show a significant improvement in forecasting error through the application of a proposed hybrid WT +FA model. The proposed hybrid wind power forecasting strategy is applied to real-life data from Kent Hill wind farm located in New Brunswick, Canada. [ABSTRACT FROM AUTHOR] |
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| Database: |
Business Source Index |