Forecasting day-ahead electricity prices using a new integrated model

Electricity price forecasting proves useful for power producers and consumers to make proper decisions in a market-oriented environment. However, due to the complex drivers and sharp fluctuation of electricity prices, accurate electricity price forecasting turns to be very difficult. To better capture the characteristics of day-ahead electricity prices, a new integrated model based on the improved empirical mode decomposition (IEMD), autoregressive moving average with exogenous terms (ARMAX), exponential generalized autoregressive conditional heteroscedasticity (EGARCH) and adaptive network-based fuzzy inference system (ANFIS) is proposed in this paper. Then it is validated by using the data from Spanish and Australian electricity markets. The results indicate that the forecasting accuracy of the new integrated model proves higher than that of some well-recognized models in the literature.