Studies with a Generalized Neuron Based PSS on a Multi-Machine Power System

An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have the drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these drawbacks, a generalized neuron based non-linear controller has been developed and illustrated as a power system stabilizer. Studies on a five machine power system show that the proposed controller can significantly improve the dynamic performance and provide good damping of the power system over a wide operating range.