BBO algorithm-based tuning of PID controller for speed control of synchronous machine

Gowrishankar Kasilingam, Pasupuleti Jagadeesh

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.

Original languageEnglish
Pages (from-to)3274-3285
Number of pages12
JournalTurkish Journal of Electrical Engineering and Computer Sciences
Volume24
Issue number4
DOIs
Publication statusPublished - 01 Jan 2016

Fingerprint

Speed control
Tuning
Derivatives
Controllers
MATLAB
Rotors

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

@article{7a9f8d5ed8f446d4bd6fd5c923aa8d2c,
title = "BBO algorithm-based tuning of PID controller for speed control of synchronous machine",
abstract = "A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.",
author = "Gowrishankar Kasilingam and Pasupuleti Jagadeesh",
year = "2016",
month = "1",
day = "1",
doi = "10.3906/elk-1501-46",
language = "English",
volume = "24",
pages = "3274--3285",
journal = "Turkish Journal of Electrical Engineering and Computer Sciences",
issn = "1300-0632",
publisher = "Turkiye Klinikleri",
number = "4",

}

BBO algorithm-based tuning of PID controller for speed control of synchronous machine. / Kasilingam, Gowrishankar; Jagadeesh, Pasupuleti.

In: Turkish Journal of Electrical Engineering and Computer Sciences, Vol. 24, No. 4, 01.01.2016, p. 3274-3285.

Research output: Contribution to journalArticle

TY - JOUR

T1 - BBO algorithm-based tuning of PID controller for speed control of synchronous machine

AU - Kasilingam, Gowrishankar

AU - Jagadeesh, Pasupuleti

PY - 2016/1/1

Y1 - 2016/1/1

N2 - A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.

AB - A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.

UR - http://www.scopus.com/inward/record.url?scp=84974698198&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84974698198&partnerID=8YFLogxK

U2 - 10.3906/elk-1501-46

DO - 10.3906/elk-1501-46

M3 - Article

VL - 24

SP - 3274

EP - 3285

JO - Turkish Journal of Electrical Engineering and Computer Sciences

JF - Turkish Journal of Electrical Engineering and Computer Sciences

SN - 1300-0632

IS - 4

ER -