Intelligent Based Power System Stabilizer for a Three Area Power System

摘要

In this paper, the authors report on the design simulation and validation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) based Power System Stabilizer (PSS) for a three area three machine system and investigate its performance in damping low frequency power system oscillations. The design employs a conventional input pairs like speed deviation (Δω) and acceleration (Δω) to the Neuro Fuzzy PSS. In this paper a first order sugeno fuzzy model, whose parameters are tuned off-line through hybrid learning algorithm is used. This algorithm is a combination of least square Estimation and Error back Propagation method. The advantage of this ANFIS based PSS is that it can be fed to each of machines in the three areas of the Power System which reduces cost, scanning time and thus simplifies the structure. It is observed that ANFIS based PSS yields a more satisfactory role in damping low frequency power system oscillations to improve the stability of power system. The performance of the system model is done using MATLB/SIMULINK.