| Title |
Daily Maximum Electric Load Forecasting for the Next 4 Weeks for Power System Maintenance and Operation |
| Authors |
정현우(Jung, Hyun-Woo) ; 송경빈(Song, Kyung-Bin) |
| DOI |
https://doi.org/10.5370/KIEE.2014.63.11.1497 |
| Keywords |
Maximum electric load ; SARIMA model ; Exponential smoothing model |
| Abstract |
Electric load forecasting is essential for stable electric power supply, efficient operation and management of power systems, and safe operation of power generation systems. The results are utilized in generator preventive maintenance planning and the systemization of power reserve management. Development and improvement of electric load forecasting model is necessary for power system maintenance and operation. This paper proposes daily maximum electric load forecasting methods for the next 4 weeks with a seasonal autoregressive integrated moving average model and an exponential smoothing model. According to the results of forecasting of daily maximum electric load forecasting for the next 4 weeks of March, April, November 2010~2012 using the constructed forecasting models, the seasonal autoregressive integrated moving average model showed an average error rate of 6,66%, 5.26%, 3.61% respectively and the exponential smoothing model showed an average error rate of 3.82%, 4.07%, 3.59% respectively. |