| Title |
Development of Peak Power Demand Forecasting Model for Special-Day using ELM |
| Authors |
지평식(Ji, Pyeong-Shik) ; 임재윤(Lim, Jae-Yoon) |
| DOI |
https://doi.org/10.5370/KIEEP.2015.64.2.074 |
| Keywords |
ELM ; Forecasting model ; Power demand ; Special-day |
| Abstract |
With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday. |