Forecasting enhancement using a Hodrick-Prescott filter

Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision-makers to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick--Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and the Fourier model, and the expected trend is obtained using simple linear regression models. Actual and generation data were used for the performance evaluation of the proposed model. The results of the current model, with improvement, showed higher accuracy as compared to ARIMA model performance.

Forecasting enhancement using a Hodrick-Prescott filter Keywords:

Forecasting , Spectrum Analysis , Hodrick-Prescott Filter