Title :
Artificial neural network based load forecasting
Author :
Momoh, James A. ; Wang, Yanchun ; Elfayoumy, M.
Author_Institution :
Center for Energy Syst. & Control, Howard Univ., Washington, DC, USA
Abstract :
The paper serves as a tutorial review on artificial neural network (ANN) applications to short-term load forecasting (STLF). Various approaches of implementation of ANN-based load forecasting are demonstrated. Two case studies using ANN-based LF were developed, one is for power system operation and the other is for load forecasting of hybrid electric vehicles (HEV). The capability of the backpropagation (BP) training algorithm has been successfully demonstrated through the case studies. The design procedure for the two cases is demonstrated step-by-step and a sample result is presented
Keywords :
backpropagation; electric vehicles; feedforward neural nets; load forecasting; multilayer perceptrons; power system CAD; artificial neural network; backpropagation; case studies; design procedure; feedforward neural network; hybrid electric vehicles; multilayer perceptron; power system operation; short-term load forecasting; training algorithm; Artificial neural networks; Control systems; Hybrid electric vehicles; Hybrid power systems; Load flow; Load forecasting; Power system analysis computing; Power system modeling; Signal analysis; Weather forecasting;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.633185
