| Title |
Weekly Maximum Electric Load Forecasting for 104 Weeks by Seasonal ARIMA Model |
| Authors |
Si-Yeon Kim ; Hyun-Woo Jung ; Jeong-Do Park ; Seung-Mook Baek ; Woo-Seon Kim ; Kyung-Hee Chon ; Kyung-Bin Song |
| DOI |
http://dx.doi.org/10.5207/JIEIE.2014.28.1.050 |
| Keywords |
Autoregressive Integrated Moving Average ; Load Pattern ; Weekly Electric Load Forecasting |
| Abstract |
Accurate midterm load forecasting is essential to preventive maintenance programs and reliable demand supply programs. This paper describes a midterm load forecasting method using autoregressive integrated moving average (ARIMA) model which has been widely used in time series forecasting due to its accuracy and predictability. The various ARIMA models are examined in order to find the optimal model having minimum error of the midterm load forecasting. The proposed method is applied to forecast 104-week load pattern using the historical data in Korea. The effectiveness of the proposed method is evaluated by forecasting 104-week load from 2011 to 2012 by using historical data from 2002 to 2010. |