Artificial Neural Network Based Self- Tunning Adaptive Power System Stabilizer

This paper presents an approach to the design of self-tuning adaptive power system stabilizer which is based on artificial neural network. Result shows that ANN based power system stabilizer can provide good damping for both local and inter area modes of oscillations. An ANN is used for self-tuning the different parameters of PSS like stabilizing gain Kstab and time constant (T1) for Lead PSS in realtime. The nodes in the input layer of the ANN receive generator terminal active power (P) and reactive power (Q). Investigations are carried out to assess the dynamic performance of the system with self-tuning PSS based on ANN (ST-ANNPSS) over a wide range of loading conditions. The neural networks possess the capability to generalize, thus, they can predict new outcomes from past trends. The Matlab/Simulink‟s neural network toolbox is used to perform the simulations. The simulation and experimental results shows the effective dynamic performance of the proposed system.