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A GARCH forecasting model to predict day-ahead electricity prices

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4 Author(s)
Garcia, R.C. ; Dept. of Energy, German Inst. of Econ. Res., Berlin, Germany ; Contreras, J. ; van Akkeren, M. ; Garcia, J.B.C.

Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize profits. This paper provides an approach to predict next-day electricity prices based on the Generalized Autoregressive Conditional Heteroskedastic (GARCH) methodology that is already being used to analyze time series data in general. A detailed explanation of GARCH models is presented and empirical results from the mainland Spain and California deregulated electricity-markets are discussed.

Published in:

Power Systems, IEEE Transactions on  (Volume:20 ,  Issue: 2 )