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

The Korean Institute of Electrical Engineers (대한전기학회)
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Short-term Electric Load Forecasting in Winter and Summer Seasons using a NARX Neural Network

NARX 신경망을 이용한 동·하계 단기부하예측에 관한 연구

  • Jeong, Hee-Myung (Dept. of Electrical Engineering, Pusan National University) ;
  • Park, June Ho (School of Electrical and Computer Engineering, Pusan National University)
  • Received : 2017.01.19
  • Accepted : 2017.06.20
  • Published : 2017.07.01
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Abstract

In this study the NARX was proposed as a novel approach to forecast electric load more accurately. The NARX model is a recurrent dynamic network. ISO-NewEngland dataset was employed to evaluate and validate the proposed approach. Obtained results were compared with NAR network and some other popular statistical methods. This study showed that the proposed approach can be applied to forecast electric load and NARX has high potential to be utilized in modeling dynamic systems effectively.

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References

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