Title :
Artificial Neural Networks Applied To Short Term Load Diagram Prediction
Author :
Hodzic, Nermin ; Konjic, Tatjana ; Miranda, Vladimiro
Author_Institution :
Center for Distance Educ. Dev., Univ. of Tuzla
Abstract :
Neural networks have broad applicability to real power system problems. One of the areas in power system with huge interest in appliance of neural networks is load forecasting. In this paper the neural networks were trained and tested using 15-minute load data collected in Portugal by the electric power company EDP during a 44 day period. The artificial neural networks showed as a good nonlinear approximator, giving promising results. The main objective of the presented work is to interest power companies in the region for possible practical implementations
Keywords :
load forecasting; neural nets; nonlinear functions; power systems; artificial neural networks; electric power company EDP; load forecasting; nonlinear approximator; power system problems; short term load diagram prediction; Artificial neural networks; Home appliances; Load forecasting; Neural networks; Power system modeling; Power system planning; Power system reliability; Power systems; Predictive models; Testing; artificial neural networks; load diagram; short term load forecast;
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on
Conference_Location :
Belgrade, Serbia & Montenegro
Print_ISBN :
1-4244-0433-9
Electronic_ISBN :
1-4244-0433-9
DOI :
10.1109/NEUREL.2006.341217
