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A Generalized Neuron Based Adaptive Power System Stabilizer For Multimachine Environment, D. K. Chaturvedi, O. P. Malik
A Generalized Neuron Based Adaptive Power System Stabilizer For Multimachine Environment, D. K. Chaturvedi, O. P. Malik
D. K. Chaturvedi Dr.
Artificial neural networks can be used as intelligent controllers to control nonlinear, dynamic systems through learning, which can easily accommodate the nonlinearities and time dependencies. Taking advantage of the characteristics of a generalized neuron (GN), that requires much smaller training data and shorter training time, a GN-based adaptive power system stabilizer (GNAPSS) is proposed. It consists of a GN as an identifier, which predicts the plant dynamics one step ahead, and a GN as a controller to damp low frequency oscillations. Results of studies with a GN-based PSS on a five-machine power system show that it can provide good damping …
A Generalized Neuron Based Pss In A Multi-Machine Power System, D. K. Chaturvedi, O. P. Malik, P. K. Kalra
A Generalized Neuron Based Pss In A Multi-Machine Power System, D. K. Chaturvedi, O. P. Malik, P. K. Kalra
D. K. Chaturvedi Dr.
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 …