SINGULAR SPECTRAL ANALYSIS APPLIED FOR SHORT TERM ELECTRICITY PRICE FORECASTING

In this paper, the data analysis and short term price forecasting in Iran electricity market as a market with pay-as-bid payment mechanism has been considered. The proposed method is a modified singular spectral analysis (SSA) method. SSA decomposes a time series into its principal components i.e. its trend and oscillation components, which are then used for time series forecasting effectively. The employed data are the experimental time series from Iran electricity market in its real size and is long enough to make it possible to take properties such as non-stationarity of market into account. The obtained results, discussed comprehensively, show that the method has a good ability in characterizing and prediction of the desired price time series.