Short-Term Electricity Price Forecast Using Frequency Analysis and Price Spikes Oversampling

This paper proposes a new short-term electricity price forecast framework using frequency analysis and price spikes oversampling. To perform normal price forecast, firstly, the variational mode decomposition (VMD) method is adopted to decompose price data into multiple frequency band-limited modes where each mode has a center frequency. Then, the extended discrete Fourier transform (EDFT) method is utilized to transform the decomposed price modes from time domain into frequency domain to predict the price. In addition, to facilitate price spike prediction, over-sampling methods including the enhanced structure preserving oversampling (ESPO) and the synthetic minority oversampling technique (SMOTE) for regression, are adopted to synthesize price spike cases. Multiple electricity markets are studied and numerous comparison results illustrate that the proposed forecast framework is capable to accurately predict both normal electricity prices and price spikes.