| Title |
Short-term demand forecasting Using Data Mining Method |
| Authors |
Sang-Yule Choi ; Hyoung-Joong Kim |
| Keywords |
Data Mining ; Power IT ; Load Forecasting ; Decision Tree |
| Abstract |
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.). Ths 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. |