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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Short-Term Power Demand Forecasting Using Information Technology Based Data Mining Method
verfasst von : Sang-Yule Choi
Erschienen in: Computational Science and Its Applications - ICCSA 2006
Verlag: Springer Berlin Heidelberg
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This paper proposes information technology based data mining to forecast short term power demand. A time-series analyses have been applied to power demand forecasting, but this method needs not only heavy computational calculation but also large amount of coefficient data. Therefore, it is hard to analyze data in fast way. To overcome time consuming process, the author take advantage of universally easily available information technology based data-mining technique to analyze patterns of days and special days(holidays, etc.). This technique consists of two steps, one is constructing decision tree, the other is estimating and forecasting power flow using decision tree analysis. To validate the efficiency, the author compares the estimated demand with real demand from the Korea Power Exchange.