Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea

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WEB OF SCIENCE

33
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SCOPUS

42

초록

In this study, we investigate the accuracy of wind-speed prediction at a designated target site using wind-speed data from reference stations that employ an ANN (artificial neural network). The reference and target sites fall into three geographical categories: plains, coast, and mountains of South Korea. Accurate wind-speed predictions are calculated by means of a correlation coefficient between the actual and simulated wind-speed data obtained by ANN. We investigate the effect of the geological characteristics of each category and the distance between reference and target sites on the accuracy of wind-speed prediction using ANN. (C) 2015 Elsevier Ltd. All rights reserved.

키워드

Wind energy; Artificial neural networks; Wind prediction; Climate data; ENERGY; MECHANISMS; PENINSULA; STATIONS; MODEL; POWER; AREA
제목
Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea
저자
Koo, Junmo; Han, Gwon Deok; Choi, Hyung Jong; Shim, Joon Hyung
DOI
10.1016/j.energy.2015.10.026
발행일
2015-12-15
유형
Article
저널명
Energy
권
93
페이지
1296 ~ 1302