This paper introduces an optimal placement and tuning of robust multi-machine Power System Stabilizer (PSS) using Honey Bee Mating Optimization (HBMO). This problem is formulated as an optimization problem, which is solved using HBMO technique. Hence the proposed approach employs HBMO to search for optimal location and parameters settings of a widely used Conventional fixed-structure lead-lag P...

In this paper, Automation of a power system fault detection using multi resolution analysis (MRA) wavelet transform is proposed and the various coefficients obtained from wavelet transform are given as an input to the probabilistic neural network (PNN). This PNN will classify and find the nature of fault occurring. Later, the decisions obtained from the output of PNN can be used to tune the pow...

A Honey Bee Mating Optimization (HBMO) technique is proposed for the optimal tuning of the Power System Stabilizer (PSS) in this paper. The design problem of robustly selecting PSS parameters is formulated as an optimization problem according to the time domain-based objective function which is solved by the HBMO technique that has a strong ability to find the most optimistic results. To achiev...

Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and RealCoded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters....

Abstract – In this paper, Genetic algorithm (GA) optimization method is presented for optimal design of power system stabilizer (PSS). The design problem of the PSS parameters is formulated as an optimization problem and GA optimization method is used to search for optimal PSS parameters. The 2-area-4-machine power system, under a wide range of system configurations and operation conditions is ...

This paper proposes a swarm intelligence method that yields optimal Proportional-Integral-Derivative (PID) Controller parameters of a power system stabilizer (PSS) in a single machine infinite bus system. The proposed method utilizes the Particle Swarm Optimization (PSO) algorithm approach to generate the optimal tuning parameters. The paper is modeled in the MATLAB Simulink Environment to anal...

This paper deals with the design of both single input and dual input conventional PSS which is used to damp the low frequency rotor oscillations taking place in power systems. The single input PSS used here are power based derivative type and speed based lead-lag type stabilizer, the dual input stabilizer, PSS3B has two inputs namely from change in speed and deviation of electrical power and ha...

This paper presents a Novel Fuzzified Multi Objective (MO) version of Honey Bee Mating Optimization (MOHBMO) approach for optimal tuning of linear parameters (such as the gain and time constant) and nonsmooth nonlinear parameters (such as saturation limits) of Power System Stabilizer (PSS). The problem of robustly tuning of PSS based SMIB design is formulated as an optimization problem accordin...

Damping of power system oscillations with the help of proposed optimal Proportional Integral Derivative Power System Stabilizer (PID-PSS) and Static Var Compensator (SVC)-based controllers are thoroughly investigated in this paper. This study presents robust tuning of PID-PSS and SVC-based controllers using Genetic Algorithms (GA) in multi machine power systems by considering detailed model of ...

This paper presents an application of the artificial intelligent search technique to find parameters optimization of power system stabilizer (PSS) considering proportional-integral-derivative controller (PID) for a multi-machine power system. Gain settings of PID PSS which improve damping frequency of system are optimized by minimizing an objective function using the artificial intelligent sear...