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Forecasting Power Prices Using a Hybrid Fundamental-Econometric Model

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3 Author(s)
Virginia Gonzalez ; Campus Universitario s/n, University of Castilla-La Mancha, Ciudad Real, Spain ; Javier Contreras ; Derek W. Bunn

We investigate the performance of two hybrid forecasting models to predict the next-day base load electricity prices on the APX power exchange for Great Britain. Hybrid models have often been advocated as a synthetic method for forecasting, but it is an open question how well they perform at the day-ahead stage. A conventional hybrid approach combines a fundamental model, formulated with supply stack modeling, with an econometric model using data on price drivers. We extend this model to one based upon logistic smooth transition regression, which represents a regime-switching for periods of structural change. Empirical results for out-of-sample forecasting using both hybrid approaches are discussed and compared to non-hybrid time series forecasting methods.

Published in:

IEEE Transactions on Power Systems  (Volume:27 ,  Issue: 1 )