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

Journal Article · Wed May 01 00:00:00 EDT 1996 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/59.496166· OSTI ID:264257

Bakirtzis, A G; Petridis, V; Kiartzis, S J; Alexiadis, M C ^[1]; Maissis, A H

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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-; ISSN 0885-8950; TRN: IM9633%%193
• Journal Information: IEEE Transactions on Power Systems, Vol. 11, Issue 2; Conference: 1995 IEEE Power Engineering Society summer meeting, Portland, OR (United States), 23-27 Jul 1995; Other Information: PBD: May 1996
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
GREECE
POWER SYSTEMS
POWER DEMAND
FORECASTING
NEURAL NETWORKS
COMPUTER CALCULATIONS