Title :
Short-term load forecasting in an autonomous power system using artificial neural networks
Author :
Kiartzis, S.J. ; Zoumas, C.E. ; Theocharis, J.B. ; Bakirtzis, A.G. ; Petridis, V.
Author_Institution :
Dept. of Electr. & Comput. Eng., Aristotelian Univ. of Thessaloniki, Greece
fDate :
11/1/1997 12:00:00 AM
Abstract :
This paper presents the development of an artificial neural network based short-term load forecasting model for an autonomous power system. Problems encountered in data preparation, network structure definition and the model´s sensitivity to temperature, together with suggested solutions, are discussed. The proposed model can provide next week´s load forecasts. Experiences obtained during the application of the model to predict daily load curves in the autonomous power system of the Greek island of Crete are presented
Keywords :
feedforward neural nets; load forecasting; power system analysis computing; Crete; Greece; artificial neural networks; autonomous power system; computer simulation; daily load curve prediction; data preparation; network structure definition; short-term load forecasting; temperature sensitivity; Artificial neural networks; Economic forecasting; Intelligent networks; Load forecasting; Power engineering and energy; Power system modeling; Power systems; Predictive models; Temperature; Weather forecasting;
Journal_Title :
Power Systems, IEEE Transactions on
