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http://dx.doi.org/10.18770/KEPCO.2016.02.04.627

Study on the Prediction of Wind Power Outputs using Curvilinear Regression  

Choy, Youngdo (KEPCO Research Institute, Korea Electric Power Corporation)
Jung, Solyoung (Department of Energygrid, Sangmyung University)
Park, Beomjun (Department of Energygrid, Sangmyung University)
Hur, Jin (Department of Energygrid, Sangmyung University)
Park, Sang ho (KEPCO Research Institute, Korea Electric Power Corporation)
Yoon, Gi gab (KEPCO Research Institute, Korea Electric Power Corporation)
Publication Information
KEPCO Journal on Electric Power and Energy / v.2, no.4, 2016 , pp. 627-630 More about this Journal
Abstract
Recently, the size of wind farms is becoming larger, and the integration of high wind generation resources into power gird is becoming more important. Due to intermittency of wind generating resources, it is an essential to predict power outputs. In this paper, we introduce the basic concept of curvilinear regression, which is one of the method of wind power prediction. The empirical data, wind farm power output in Jeju Island, is considered to verify the proposed prediction model.
Keywords
Wind Power Outputs; Wind Power Predict; Linear Regression; Curvilinear Regression;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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