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Short-term electric load forecasting using data mining technique

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6 Author(s)
Koo, Bon-Gil ; Department of Electrical and Electronic Engineering, Pusan National University, Korea ; Kim, Min-Seok ; Kim, Kyu-Han ; Lee, Hee-Tae
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In this paper, the short-term load forecast is conducted by utilizing SARIMA model and Holt-Winters model including load classification by use of k-NN algorithm. With embodiment of a load classification procedure, it could be possible to provide more accurate load data. After load classification using 1-year training set and 1-year test set, forecast was performed through the two models. Although the differences in the results were minor, by measuring their MAPE, Holt-Winters was shown to have better performance in short-term load forecasting.

Published in:

Intelligent Systems and Control (ISCO), 2013 7th International Conference on

Date of Conference:

4-5 Jan. 2013