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ANN application techniques for power system stability estimation
Electric Power Components and Systems (2000)
  • Prof Mahmoud Moghavvemi, University of Malaya
  • S.S. Yang

The implementation of artificial neural networks (ANN) as a power system stability monitoring tool is a viable option, introducing dynamic and intelligent solution to utility operators. This paper examines the performance of two nonlinear multilayer ANN models which are similar in structural topology and training emphasis but different by way of the utilization of their net or basis function. The performance of both models were compared for the estimation of stability index to gauge the stability of a power system network. Although tests were conducted in a simulated environment, loading patterns analyzed in this case study were realistically generated, and hence test results realistically accentuates the potential of ANN for practical on-line dynamic system implementation. Copyright © 2000 Taylor & Francis.

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Prof Mahmoud Moghavvemi and S.S. Yang. "ANN application techniques for power system stability estimation" Electric Power Components and Systems Vol. 28 Iss. 2 (2000)
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