Statistical Modeling for Forecasting Maximum Electricity Demand in Korea Yoon, Sang-Hoo; Lee, Young-Saeng; Park, Jeong-Soo;
It is necessary to forecast the amount of the maximum electricity demand for stabilizing the flow of electricity. The time series data was collected from the Korea Energy Research between January 2000 and December 2006. The data showed that they had a strong linear trend and seasonal change. Winters seasonal model, ARMA model were used to examine it. Root mean squared prediction error and mean absolute percentage prediction error were a criteria to select the best model. In addition, a nonstationary generalized extreme value distribution with explanatory variables was fitted to forecast the maximum electricity.
RMSE;Winters seasonal model;ARMA model;additional explanatory variable;generalized extreme value distribution;