| Title |
TAR(Threshold Autoregressive) Model for Short-Term Load Forecasting Using Nonlinearity of Temperature and Load |
| Authors |
이경훈(Lee, Gyeong-Hun) ; 이윤호(Lee, Yun-Ho) ; 김진오(Kim, Jin-O) |
| Keywords |
Short-term load forecasting ; TAR(Threshold Autoregressive) model |
| 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. |