Feature extraction of meteorological data using regression tree for wind power generation

Hiroyuki Mori, Akira Awata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008
Pages1104-1107
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2008
Event2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008 - Singapore, Singapore
Duration: 24 Nov 200827 Nov 2008

Publication series

Name2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008

Conference

Conference2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008
CountrySingapore
CitySingapore
Period24/11/0827/11/08

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  • Cite this

    Mori, H., & Awata, A. (2008). Feature extraction of meteorological data using regression tree for wind power generation. In 2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008 (pp. 1104-1107). [4747171] (2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008). https://doi.org/10.1109/ICSET.2008.4747171