Title :
Power system preventive control using artificial neural network based generation rescheduling method
Author :
Effiong, Chris B. ; Momoh, James A.
Author_Institution :
Dept. of Electr. Eng., Howard Univ., Washington, DC, USA
Abstract :
A method for computing generation rescheduling for preventive control using artificial neural network (ANN) and transient energy margin (EM) is proposed. A two stage hybrid paradigm is used first to obtain the energy margin sensitivities with respect to generation and second to obtain the generation shift for rescheduling. The sensitivities are derived from the final connecting weights of the ANN.
Keywords :
backpropagation; feedforward neural nets; neurocontrollers; power system control; scheduling; artificial neural network; final connecting weights; generation rescheduling method; power system preventive control; rescheduling; transient energy margin; two stage hybrid paradigm; Artificial neural networks; Computer networks; Control systems; Hybrid power systems; Power generation; Power system control; Power system security; Power system transients; Power systems; System testing;
Conference_Titel :
Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
Print_ISBN :
0-7803-3694-1
DOI :
10.1109/MWSCAS.1997.662354
