Gowrishankar Kasilingam

Implementation and Analysis of BBO Algorithm for Better Damping of Rotor Oscillations of a Synchronous Machine

In this paper, a new evolutionary algorithm, namely the biogeography-based optimization (BBO) algorithm, is proposed to tune the Proportional Integral Derivative (PID) controller and power system stabilizer (PSS) parameters. The efficiency of BBO algorithm is verified on the single-machine infinite-bus (SMIB) system for various operating conditions. The proposed method suppresses the (0.1–2.5 Hz) low-frequency electromechanical oscillations and increases the power system stability via minimizing the objective function such as integral square error (ISE). Simulations of BBO-based PID, BBO-based PSS, BBO-based PID-PSS and conventional PSS are performed by using MATLAB/Simulink. The results show that BBO-based PID-PSS method improves the system performance and provides better dynamic performance.

Auto tuning of PID controller of a synchronous machine connected to a linear and non linear load

A proportional-integral-derivative (PID)-based power system stabilizer (PSS) is connected to the excitation system for stability enhancement of a single machine power system. In this paper, an auto-tuning of PID controller with PSS has been proposed to damp out the low frequency oscillations in the synchronous machine. Tuning the PID gains of the controller is considered as the optimization problem, and the parameters are tuned using Adaptation law. Recursive Least Square (RLS) Identifier has been used to estimate the real time parameters for tuning PID gains. The proposed PID type PSS is thoroughly investigated for fixed RLC linear load and three phase thyristor based nonlinear load with different kinds of faults. The performance of the synchronous machine such as speed deviation, load angle and rotor angle deviation were analyzed in MATLAB Simulink based environment.