Journal
IFAC PAPERSONLINE
Volume 51, Issue 28, Pages 678-683Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ifacol.2018.11.783
Keywords
Short-term load forecast; power system operation; artificial neural network; load adjustment; day-ahead electricity market
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Short-term load forecast (STLF) is important to ensure stable, reliable and efficient power system operations. In this paper, we propose a two-stage artificial neural network (ANN) model for load forecasting application. The proposed system is currently being tested in the Taiwan Power Company (TPC) with potential for future adoption in their decision support systems. The accuracy of the proposed forecast model is tested using the historical data obtained from TPC; the results show that the proposed two-stage ANN model can outperform a previously proposed single stage ANN load forecast model. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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