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Electricity price short-term forecasting using artificial neural networks

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3 Author(s)
Szkuta, B.R. ; Appl. Comput. Res. Inst., La Trobe Univ., Melbourne, Vic., Australia ; Sanabria, L.A. ; Dillon, T.S.

This paper presents the system marginal price (SMP) short-term forecasting implementation using the artificial neural networks (ANN) computing technique. The described approach uses the three-layered ANN paradigm with backpropagation. The retrospective SMP real-world data, acquired from the deregulated Victorian power system, was used for training and testing the ANN. The results presented in this paper confirm considerable value of the ANN based approach in forecasting the SMP

Published in:

Power Systems, IEEE Transactions on  (Volume:14 ,  Issue: 3 )

Date of Publication:

Aug 1999

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