Title :
A neural network short term load forecasting model for the Greek power system
Author :
Bakirtzis, Anastasios G. ; Petridis, V. ; Kiartzis, S.J. ; Alexiadis, Minas C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Aristotelian Univ. of Thessaloniki
fDate :
5/1/1996 12:00:00 AM
Abstract :
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
Keywords :
learning (artificial intelligence); load forecasting; neural nets; power system analysis computing; ANN structure; Greece; accuracy; artificial neural network; holiday modelling; input variables selection; power systems; short term load forecasting model; training data set; Artificial neural networks; Costs; Economic forecasting; Input variables; Load forecasting; Load modeling; Neural networks; Neurons; Power system modeling; Predictive models; Temperature distribution; Training data;
Journal_Title :
Power Systems, IEEE Transactions on
