DocumentCode :
2345744
Title :
Feature extraction of meteorological data using regression tree for wind power generation
Author :
Mori, Hiroyuki ; Awata, Akira
Author_Institution :
Dept. of Electron. & Bioinf., Meiji Univ., Kawasaki
fYear :
2008
fDate :
24-27 Nov. 2008
Firstpage :
1104
Lastpage :
1107
Abstract :
This paper proposes a feature extraction method for weather conditions of wind power generation. The proposed method makes use of the regression tree to classify input variables and extract rules. In recent years, power system operations are interested in renewable energy such as wind power generation from a standpoint of environment conservation. In that sense, wind power generation is widely-spread in the world. The operation of wind power generation is affected by the weather conditions. In this paper, the relationship between the wind speed and other variables is clarified by the regression tree. The proposed method is tested for real data.
Keywords :
feature extraction; regression analysis; wind power plants; feature extraction; meteorological data; power system operations; regression tree; renewable energy; weather conditions; wind power generation; Classification tree analysis; Data mining; Feature extraction; Input variables; Meteorology; Power systems; Regression tree analysis; Renewable energy resources; Wind power generation; Wind speed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sustainable Energy Technologies, 2008. ICSET 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1887-9
Electronic_ISBN :
978-1-4244-1888-6
Type :
conf
DOI :
10.1109/ICSET.2008.4747171
Filename :
4747171
Link To Document :
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