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A neural network short term load forecasting model for the Greek power system

Journal Article · · IEEE Transactions on Power Systems
DOI:https://doi.org/10.1109/59.496166· OSTI ID:264257
; ; ;  [1];
  1. Aristotle Univ. of Thessaloniki (Greece). Dept. of Electrical and Computer Engineering

This paper presents the development of an Artificial Neural Network (ANN) based short-term load forecasting model for the Energy Control Center of the Greek Public Power Corporation (PPC). The model can forecast daily load profiles with a lead time of one to seven days. Attention was paid for the accurate modeling of holidays. Experiences gained during the development of the model regarding the selection of the input variables, the ANN structure, and the training data set are described in the paper. The results indicate that the load forecasting model developed provides accurate forecasts.

OSTI ID:
264257
Report Number(s):
CONF-950727--
Journal Information:
IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 2 Vol. 11; ISSN ITPSEG; ISSN 0885-8950
Country of Publication:
United States
Language:
English

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