TAR(Threshold Autoregressive) Model for Short-Term Load Forecasting Using Nonlinearity of Temperature and Load

온도와 부하의 비선형성을 이용한 단기부하예측에서의 TAR(Threshold Autoregressive) 모델

  • 이경훈 (한양대 대학원 전기공학과) ;
  • 이윤호 (한양대 대학원 전기공학과 연구원) ;
  • 김진오 (한양대 전기공학과)
  • Published : 2001.09.01

Abstract

This paper proposes TAR(Threshold Autoregressive) model for short-term load forecasting including temperature variable. In the scatter diagram of daily peak load versus daily high or low temperature, we can find out that the load-temperature relationship has a negative slope in the lower regime and a positive slope in the upper regime due to the heating and cooling load, respectively. TAR model is adequate for analyzing these phenomena since TAR model is a piecewise linear autoregressive model. In this paper, we estimated and forecasted one day-ahead daily peak load by applying TAR model using this load-temperature characteristic in these regimes. The results are compared with those of linear and quadratic regression models.

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