TY - GEN
T1 - Application of neural networks to automatic load frequency control
AU - Nag, Soumyadeep
AU - Philip, Namitha
PY - 2013
Y1 - 2013
N2 - This paper is intended to present the benefits of the application of artificial neural network to automatic load frequency control. The power system model has been simulated and the conventional PI controller has been replaced by the artificial neural network controller wherein, we have trained the neural controller to behave as a PI controller. The strategy has been successfully tested for both a single area as well as multi area systems using MATLAB/SIMULINK. With the help of a neural controller we have been able to achieve a smaller transient dip as well as faster stabilization of frequency.
AB - This paper is intended to present the benefits of the application of artificial neural network to automatic load frequency control. The power system model has been simulated and the conventional PI controller has been replaced by the artificial neural network controller wherein, we have trained the neural controller to behave as a PI controller. The strategy has been successfully tested for both a single area as well as multi area systems using MATLAB/SIMULINK. With the help of a neural controller we have been able to achieve a smaller transient dip as well as faster stabilization of frequency.
UR - https://www.scopus.com/pages/publications/84893304011
U2 - 10.1007/978-3-319-03756-1_39
DO - 10.1007/978-3-319-03756-1_39
M3 - Conference contribution
AN - SCOPUS:84893304011
SN - 9783319037554
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 431
EP - 441
BT - Swarm, Evolutionary, and Memetic Computing - 4th International Conference, SEMCCO 2013, Proceedings
T2 - 4th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2013
Y2 - 19 December 2013 through 21 December 2013
ER -