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Title: Electricity price short-term forecasting using artificial neural networks

Journal Article · · IEEE Transactions on Power Systems
DOI:https://doi.org/10.1109/59.780895· OSTI ID:678006
; ;  [1]
  1. La Trobe Univ., Melbourne (Australia). Applied Computing Research Inst.

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 back-propagation. 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.

OSTI ID:
678006
Journal Information:
IEEE Transactions on Power Systems, Vol. 14, Issue 3; Other Information: PBD: Aug 1999
Country of Publication:
United States
Language:
English