Neural networks for designing an automatic voltage regulator of a synchronous generator

Automatic voltage regulators (AVRs) are controllers used to maintain consistent voltage at the generator terminals. In general these controllers are designed using linear models. However, power systems are extremely nonlinear and highly complex. Therefore, using nonlinear techniques to design AVR would seem more appropriate. Artificial Neural Networks (ANNs) are nonlinear maps that have the potential to finally make the realisation of practical nonlinear controllers possible. This paper is concerned with the development of a Feedforward Multilayer Perceptron (MLP) Neural Networks and its use as an Automatic Voltage Regulator (AVR) with Power System Stabiliser (PSS). The performance of the MLP-AVR is compared with a conventional AVR. The MLP-AVR shows good performance compared to that of conventional AVR.

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