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A Generalized Neuron Based PSS in A Multi-Machine Power System
IEEE Trans. of Energy Conversions (2004)
  • D. K. Chaturvedi, Dayalbagh Educational Institute
  • O. P. Malik
  • P. K. Kalra
An artificial neural network can work as an intelligent controller for nonlinear dynamic systems through learning, as it can easily accommodate the nonlinearities and time dependencies. In dealing with complex problems, most common neural networks have some drawbacks of large training time, large number of neurons and hidden layers. These drawbacks can be overcome by a nonlinear controller based on a generalized neuron (GN) which retains the quick response of neural net. Results of studies with a GN-based power system stabilizer on a five-machine power system show that it can provide good damping over a wide operating range and significantly improve the dynamic performance of the system.
  • Generalized neuron (GN),
  • low-frequency oscillation,
  • neural network,
  • neuro-PSS,
  • power system stabilizer
Publication Date
September, 2004
Citation Information
D. K. Chaturvedi, O. P. Malik and P. K. Kalra. "A Generalized Neuron Based PSS in A Multi-Machine Power System" IEEE Trans. of Energy Conversions Vol. 19 Iss. 3 (2004)
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