Implementation of an Innovative Bio Inspired GA and PSO Algorithm for Controller design considering Steam GT Dynamics

TL;DR

This paper introduces a novel bio-inspired genetic and particle swarm optimization approach for designing controllers that enhance power system stability by damping low frequency oscillations, including detailed modeling of Steam GT dynamics.

Contribution

It presents a new systematic method using bio-inspired algorithms for optimal controller design considering Steam GT dynamics in power systems.

Findings

Bio-inspired controllers outperform conventional controllers in damping oscillations.

The proposed method improves system stability under various operating conditions.

Simulation results confirm robustness and effectiveness of the algorithms.

Abstract

The Application of Bio Inspired Algorithms to complicated Power System Stability Problems has recently attracted the researchers in the field of Artificial Intelligence. Low frequency oscillations after a disturbance in a Power system, if not sufficiently damped, can drive the system unstable. This paper provides a systematic procedure to damp the low frequency oscillations based on Bio Inspired Genetic (GA) and Particle Swarm Optimization (PSO) algorithms. The proposed controller design is based on formulating a System Damping ratio enhancement based Optimization criterion to compute the optimal controller parameters for better stability. The Novel and contrasting feature of this work is the mathematical modeling and simulation of the Synchronous generator model including the Steam Governor Turbine (GT) dynamics. To show the robustness of the proposed controller, Non linear Time domain simulations have been carried out under various system operating conditions. Also, a detailed Comparative study has been done to show the superiority of the Bio inspired algorithm based controllers over the Conventional Lead lag controller.