Abstract
The demand of power and the size and complexity of the power system is increasing. Wide area monitoring and control is an integral part in transitioning from the traditional power system to a Smart Grid. However, wide area monitoring becomes challenging as the size of the electric power grid, and consequently the number of components to be monitored, grows. Wide area monitor (WAM) designed using feed-forward and feedback neural network architectures do not scale up to handle the growing complexity of the Smart Grid. in this paper, cellular neural network (CNN) is presented as a way to provide scalability in the development of a WAM for Smart Grid. the CNN based WAM is compared with multilayer perceptron's (MLP) based WAM on two different power systems. the results show that the CNN has better or comparable performance with, and scales up much better than, MLP. © 2011 IEEE.
Recommended Citation
B. Luitel and G. K. Venayagamoorthy, "Wide Area Monitoring in Power Systems using Cellular Neural Networks," IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CIASG 2011: 2011 IEEE Symposium on Computational Intelligence Applications in Smart Grid, pp. 96 - 103, article no. 5953343, Institute of Electrical and Electronics Engineers, Aug 2011.
The definitive version is available at https://doi.org/10.1109/CIASG.2011.5953343
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Backpropagation; Cellular Multilayer Perceptron; CNN; MIMO; Power system; Wide Area Monitor
International Standard Book Number (ISBN)
978-142449894-9
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
17 Aug 2011
