Please use this identifier to cite or link to this item:
http://idr.iitbbs.ac.in/jspui/handle/2008/84
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mishra S. | en_US |
dc.contributor.author | Sharma A. | en_US |
dc.contributor.author | Panda G. | en_US |
dc.date.accessioned | 2020-01-13T05:19:27Z | - |
dc.date.available | 2020-01-13T05:19:27Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | 3 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1109/ICEAS.2011.6147151 | - |
dc.identifier.uri | http://10.10.32.48:8080/jspui/handle/2008/84 | - |
dc.description.abstract | Due to growing share of wind power in world's energy consumption, forecasting of the wind power becomes essential for proper utilization. This paper proposes short term wind power forecasting model using complex wavelet transform and neural network. The past wind power values are transferred into real and complex signal; which are further transferred in Wavelet domain signal. These signals are used to predict next hour wind power using neural network. This approach is tested using data from Alberta wind farm. � 2011 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.subject | Complex wavelet | en_US |
dc.subject | Neural network | en_US |
dc.subject | Wind Power forecasting | en_US |
dc.title | Wind power forecasting model using complex wavelet theory | en_US |
dc.type | Conference Paper | en_US |
Appears in Collections: | Research Publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.