Title :
Forecasting the algerian load peak profile using time series model based on backpropagation neural networks
Author :
Abdellah, Draidi ; Djamel, Labed
Author_Institution :
Dept. of Electr. Eng., Univ. of Constantine, Constantine, Algeria
Abstract :
Load forecasting has many applications for power systems, including energy purchasing and generation, load switching, contract evaluation, and infrastructure development. In this paper, we will discuss night peak load forecasting of Algerian power system using time series back propagation neural networks, including the effect of the temperature, working days and weekends.
Keywords :
backpropagation; load forecasting; neural nets; power engineering computing; purchasing; time series; Algerian load peak forecasting; Algerian power system; backpropagation neural networks; contract evaluation; energy generation; energy purchasing; infrastructure development; load switching; power systems; time series back propagation neural networks; time series model; Biological neural networks; Forecasting; Load forecasting; Load modeling; Neurons; Predictive models; Time series analysis; Load forecasting; neural networks; power systems; temperature; time series model; weekend; working day;
Conference_Titel :
Power Engineering, Energy and Electrical Drives (POWERENG), 2013 Fourth International Conference on
Conference_Location :
Istanbul
DOI :
10.1109/PowerEng.2013.6635879
