Exogenous Variable Considered Generalized Autoregressive Conditional Heteroscedastic Model for Day-Ahead Electricity Price Forecasting

The authors forecast day-ahead electricity price by generalized autoregressive conditional heteroscedasticity(GARCH) model and as exogenous variable the daily price ratios of different weekday types are led into this GARCH mode to intensify the response of the proposed model to external influences. Using the proposed model,the day-ahead electricity prices of PJM(Pennsylvania-New Jersey-Maryland) electricity market in December 2004 are forecasted. Forecasting results show that the forecasted day-ahead electricity prices in peak hours are evidently better than those by other models taken for contrasts,and its global forecasting precision is also better than those by other models.