The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Short-Term Load Forecast for Summer Special Light-Load Period

하계 특수경부하기간의 단기 전력수요예측

  • Park, Jeong-Do (Division of Energy & Electrical Engineering, Uiduk University) ;
  • Song, Kyung-Bin (Dept. of Electrical Engineering, Soongsil University)
  • 박정도 (위덕대학교 에너지전기공학부) ;
  • 송경빈 (숭실대학교 전기공학부)
  • Received : 2013.02.07
  • Accepted : 2013.03.13
  • Published : 2013.04.01
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Abstract

Load forecasting is essential to the economical and the stable power system operations. In general, the forecasting days can be classified into weekdays, weekends, special days and special light-load periods in short-term load forecast. Special light-load periods are the consecutive holidays such as Lunar New Years holidays, Korean Thanksgiving holidays and summer special light-load period. For the weekdays and the weekends forecast, the conventional methods based on the statistics are mainly used and show excellent results for the most part. The forecast algorithms for special days yield good results also but its forecast error is relatively high than the results of the weekdays and the weekends forecast methods. For summer special light-load period, none of the previous studies have been performed ever before so if the conventional methods are applied to this period, forecasting errors of the conventional methods are considerably high. Therefore, short-term load forecast for summer special light-load period have mainly relied on the experience of power system operation experts. In this study, the trends of load profiles during summer special light-load period are classified into three patterns and new forecast algorithms for each pattern are suggested. The proposed method was tested with the last ten years' summer special light-load periods. The simulation results show the excellent average forecast error near 2%.

Keywords

References

  1. Kyung-Bin Song, Bon-Suk Ku, Young-Sik Baek, "Load Forecasting for Holidays Using a Fuzzy Least Squares Linear Regression Algorithm", The Transaction of the KIEE, Vol.52 No.4 , pp 233-237, 2003
  2. Kwang-Ho Kim, Hyoung-Sun Youn, Yong-Cheol Kang, "Short-Term Load Forecasting for Special Days in Anomalous Load Conditions Using Neural Networks and Fuzzy Inference Method", IEEE Transaction on Power Systems, Vol. 15 No.2, pp 559-565, May 2000 https://doi.org/10.1109/59.867141
  3. Saeid Nahi, "Load Forecasting on Special Days & Holidays in Power Distribution Substation Using Neural & Fuzzy Networks", IEEE International Conference on Computational Intelligence for Modeling Control and Automation, Conference Publication, pp 118, Nov 2006
  4. I. Aquino, C. Perez, J.K. Chavez, S. Oporto, "Daily Load Forecasting Using Quick Propagation Neural Network with a Special Holiday Encoding", IJCNN, Conference Publications, pp 1935-1940, Aug 2007
  5. Yuanzhe Cai, Qing Xie, Chengqiang Wang, Fang-cheng Lu, "Short-term load forecasting for city holidays based on genetic support vector machines", ICECE 2011, Conference Publications, pp 3144-3147, Sep 2011
  6. Korea Power Exchange, "Electricity Market Rules", Dec 2011
  7. Kyung-Bin Song, Seong-Kwan Ha, "An Algorithm of Short-Term Load Forecasting", Trans. of KIEE, Vol. 53A, No. 10, pp.529-535, Oct 2004
  8. Kyung-Bin Song, Oh-Sung Kwon, Jeong-Do Park, "Optimal Coefficient Selection of Exponential Smoothing Model in Short Term Load Forecasting on Weekdays", Trans. of KIEE, Vol. 62, No. 2, pp.149-154, Feb 2013
  9. Jeong-Do Park, Kyung-Bin Song, Hyeong-Woo Lim, Hae-Soo Park, "Short-Term Load Forecast for Near Consecutive Holidays Having The Mixed Load Profile Characteristics of Weekdays and Weekends", Trans. of KIEE, Vol. 61, No. 12, pp.1765-1773, Dec 2012

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