Spectral decomposition of variations in electricity loading using mixed radix fast Fourier transform

A frequency-domain approach to forecasting is presented, which is suitable for time series that have harmonically related frequency components. It involves the use of a fast Fourier transform algorithm that calculates the frequency spectrum of a discrete set of data points whose array size is not restricted to the set 2m, where m is an integer. The high resolution of the spectra obtained for New Zealand Electricity short- and medium-term data enables the true components present in the time-domain waveforms to be accurately identified. A modified time-domain waveform by inverse transforming is then determined, which (containing only the true harmonic components) can be extrapolated to yield a forecast.