Optimal Coefficient Selection of Exponential Smoothing Model in Short Term Load Forecasting on Weekdays

평일 단기전력수요 예측을 위한 최적의 지수평활화 모델 계수 선정

  • Song, Kyung-Bin (Department of Electrical Engineering, Soongsil University) ;
  • Kwon, Oh-Sung (Department of Electrical Engineering, Soongsil University) ;
  • Park, Jeong-Do (Division of Energy & Electrical Engineering, Uiduk University)
  • 송경빈 (숭실대학교 전기공학과) ;
  • 권오성 (숭실대학교 전기공학과) ;
  • 박정도 (위덕대학교 에너지전기공학부)
  • Received : 2012.07.03
  • Accepted : 2012.12.27
  • Published : 2013.02.01


Short term load forecasting for electric power demand is essential for stable power system operation and efficient power market operation. High accuracy of the short term load forecasting can keep the power system more stable and save the power market operation cost. We propose an optimal coefficient selection method for exponential smoothing model in short term load forecasting on weekdays. In order to find the optimal coefficient of exponential smoothing model, load forecasting errors are minimized for actual electric load demand data of last three years. The proposed method are verified by case studies for last three years from 2009 to 2011. The results of case studies show that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.


Supported by : 한국에너지기술평가원(KETEP)


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