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KMID : 1024520100190101229
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Journal of the Environmental Sciences
2010 Volume.19 No. 10 p.1229 ~ p.1235
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Cluster Analysis and Meteor-Statistical Model Test to Develop a Daily Forecasting Model for Jejudo Wind Power Generation
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Kim Hyun-Goo
Lee Yung-Seop
Jang Moon-Seok
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Abstract
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Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.
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KEYWORD
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Wind power forecasting, Cluster analysis, Meteor-statistical forecasting model, Jejudo
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