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Proceedings of the First International Forum on Applications of Neural Networks to Power Systems (Cat. No.91TH0374-9)

A study on neural networks for short-term load forecasting

Content Provider	IEEE Xplore Digital Library
Author	Lee, K.Y. Cha, Y.T. Ku, C.C.
Copyright Year	1991
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Pennsylvania State Univ., University Park, PA, USA (Lee, K.Y.; Cha, Y.T.; Ku, C.C.)
Abstract	A study is made on the application of the artificial neural network (ANN) method to forecast the short-term load for a large power system. The load has two distinct patterns: weekday and weekend-day patterns. The weekend-day pattern include Saturday, Sunday, and Monday loads. Three different ANN models are proposed, including two feedforward neural networks and one recurrent neural network. Inputs to the ANN are past loads and the output is the predicted load for a given day. The standard deviation and percent error of each model are compared.
Starting Page	26
Ending Page	30
File Size	399605
Page Count	5
File Format	PDF
ISBN	0780300653
DOI	10.1109/ANN.1991.213492
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-07-23
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Load forecasting Artificial neural networks Load modeling Weather forecasting Backpropagation algorithms Power system modeling Recurrent neural networks Predictive models Application software
Content Type	Text
Resource Type	Article

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