Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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Short-Term Forecasting of Monthly Maximum Electric Power Loads Using a Winters' Multiplicative Seasonal Model

Winters' Multiplicative Seasonal Model에 의한 월 최대 전력부하의 단기예측

  • Yang, Moonhee (Department of Industrial Engineering, Donkook University) ;
  • Lim, Sanggyu (Department of Industrial Systems Engineering, Gyeongsang National University)
  • 양문희 (단국대학교 산업공학과) ;
  • 임상규 (경상대학교 산업시스템공학부)
  • Published : 2002.03.31
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Abstract

To improve the efficiency of the electric power generation, monthly maximum electric power consumptions for a next one year should be forecasted in advance and used as the fundamental input to the yearly electric power-generating master plan, which has a greatly influence upon relevant sub-plans successively. In this paper, we analyze the past 22-year hourly maximum electric load data available from KEPCO(Korea Electric Power Corporation) and select necessary data from the raw data for our model in order to reflect more recent trends and seasonal components, which hopefully result in a better forecasting model in terms of forecasted errors. After analyzing the selected data, we recommend to KEPCO the Winters' multiplicative model with decomposition and exponential smoothing technique among many candidate forecasting models and provide forecasts for the electric power consumptions and their 95% confidence intervals up to December of 1999. It turns out that the relative errors of our forecasts over the twelve actual load data are ranged between 0.1% and 6.6% and that the average relative error is only 3.3%. These results indicate that our model, which was accepted as the first statistical forecasting model for monthly maximum power consumption, is very suitable to KEPCO.

Keywords

References

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