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Short-term Electrical Load Forecasting Using Neuro-Fuzzy Model with Error Compensation

Wang, Bo-Hyeun    (Department of Electrical Engineering, Kangnung-Wonju National University  );
  • 초록

    This paper proposes a method to improve the accuracy of a short-term electrical load forecasting (STLF) system based on neuro-fuzzy models. The proposed method compensates load forecasts based on the error obtained during the previous prediction. The basic idea behind this approach is that the error of the current prediction is highly correlated with that of the previous prediction. This simple compensation scheme using error information drastically improves the performance of the STLF based on neuro-fuzzy models. The viability of the proposed method is demonstrated through the simulation studies performed on the load data collected by Korea Electric Power Corporation (KEPCO) in 1996 and 1997.


  • 주제어

    Load forecasting .   Neuro-fuzzy model .   Structure identification .   Compensation by prediction error.  

  • 참고문헌 (21)

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  • 이 논문을 인용한 문헌 (3)

    1. 2013. "" International journal of fuzzy logic and intelligent systems : IJFIS, 13(1): 39~49     
    2. Jang, Sang-Bok ; Lee, Ho-Hyun ; Lee, Dae-Jong ; Kweon, Jin-Hee ; Chun, Myung-Geun 2015. "Development of Sludge Concentration Estimation Method using Neuro-Fuzzy Algorithm" 한국지능시스템학회 논문지 = Journal of Korean institute of intelligent systems, 25(2): 119~125     
    3. Lee, Ho-Hyun ; Shin, Gang-Wook ; Hong, Sung-Taek ; Chun, Myung-Geun 2015. "Intelligent Controller for Optimal Coagulant Dosage Rate in Water Treatment Process" 한국지능시스템학회 논문지 = Journal of Korean institute of intelligent systems, 25(4): 369~376     

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