Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances

Gowrishankar Kasilingam, Pasupuleti Jagadeesh, C. Bharatiraja, Yusuff Adedayo

Research output: Contribution to journalArticle

Abstract

In a practical power system, the synchronous generators should cope with changes in both real and reactive power demand. In general, stabilization of real power variations is possible by rescheduling the operation of generators. To control the demand of the reactive power load, electric limits of the excitation loop is adjusted to initiate the reactive power of the network. In order to accelerate the reactive power delivery, a power system stabilizer (PSS) is connected to the generator through an exciter. We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. This is possible when the integral square error (ISE), which is the objective function, of the speed deviation in asynchronous machine intended to a range of turbulence is reduced. A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. The simulation results indicate that when compared to other available methods, the BBO algorithm damps out low-frequency oscillations in the synchronous machine rotor in an effective manner. Algorithms are simulated with the help of MATLAB®and Simulink®. Results obtained from simulations indicate that the recommended algorithm yields rapid convergence rate and improved dynamic performance; system stability, efficiency, dynamism and reliability are also improved.

Original languageEnglish
Pages (from-to)166-176
Number of pages11
JournalFME Transactions
Volume47
Issue number1
DOIs
Publication statusPublished - 01 Jan 2019

Fingerprint

Reactive power
Rotors
Damping
Electric loads
Synchronous generators
System stability
Particle swarm optimization (PSO)
Turbulence
Stabilization

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering

Cite this

@article{b7a4f442f791423bb16880531f290010,
title = "Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances",
abstract = "In a practical power system, the synchronous generators should cope with changes in both real and reactive power demand. In general, stabilization of real power variations is possible by rescheduling the operation of generators. To control the demand of the reactive power load, electric limits of the excitation loop is adjusted to initiate the reactive power of the network. In order to accelerate the reactive power delivery, a power system stabilizer (PSS) is connected to the generator through an exciter. We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. This is possible when the integral square error (ISE), which is the objective function, of the speed deviation in asynchronous machine intended to a range of turbulence is reduced. A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. The simulation results indicate that when compared to other available methods, the BBO algorithm damps out low-frequency oscillations in the synchronous machine rotor in an effective manner. Algorithms are simulated with the help of MATLAB{\circledR}and Simulink{\circledR}. Results obtained from simulations indicate that the recommended algorithm yields rapid convergence rate and improved dynamic performance; system stability, efficiency, dynamism and reliability are also improved.",
author = "Gowrishankar Kasilingam and Pasupuleti Jagadeesh and C. Bharatiraja and Yusuff Adedayo",
year = "2019",
month = "1",
day = "1",
doi = "10.5937/fmet1901166K",
language = "English",
volume = "47",
pages = "166--176",
journal = "FME Transactions",
issn = "1451-2092",
publisher = "Faculty of Mechanical Engineering, Belgrade University",
number = "1",

}

Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances. / Kasilingam, Gowrishankar; Jagadeesh, Pasupuleti; Bharatiraja, C.; Adedayo, Yusuff.

In: FME Transactions, Vol. 47, No. 1, 01.01.2019, p. 166-176.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances

AU - Kasilingam, Gowrishankar

AU - Jagadeesh, Pasupuleti

AU - Bharatiraja, C.

AU - Adedayo, Yusuff

PY - 2019/1/1

Y1 - 2019/1/1

N2 - In a practical power system, the synchronous generators should cope with changes in both real and reactive power demand. In general, stabilization of real power variations is possible by rescheduling the operation of generators. To control the demand of the reactive power load, electric limits of the excitation loop is adjusted to initiate the reactive power of the network. In order to accelerate the reactive power delivery, a power system stabilizer (PSS) is connected to the generator through an exciter. We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. This is possible when the integral square error (ISE), which is the objective function, of the speed deviation in asynchronous machine intended to a range of turbulence is reduced. A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. The simulation results indicate that when compared to other available methods, the BBO algorithm damps out low-frequency oscillations in the synchronous machine rotor in an effective manner. Algorithms are simulated with the help of MATLAB®and Simulink®. Results obtained from simulations indicate that the recommended algorithm yields rapid convergence rate and improved dynamic performance; system stability, efficiency, dynamism and reliability are also improved.

AB - In a practical power system, the synchronous generators should cope with changes in both real and reactive power demand. In general, stabilization of real power variations is possible by rescheduling the operation of generators. To control the demand of the reactive power load, electric limits of the excitation loop is adjusted to initiate the reactive power of the network. In order to accelerate the reactive power delivery, a power system stabilizer (PSS) is connected to the generator through an exciter. We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. This is possible when the integral square error (ISE), which is the objective function, of the speed deviation in asynchronous machine intended to a range of turbulence is reduced. A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. The simulation results indicate that when compared to other available methods, the BBO algorithm damps out low-frequency oscillations in the synchronous machine rotor in an effective manner. Algorithms are simulated with the help of MATLAB®and Simulink®. Results obtained from simulations indicate that the recommended algorithm yields rapid convergence rate and improved dynamic performance; system stability, efficiency, dynamism and reliability are also improved.

UR - http://www.scopus.com/inward/record.url?scp=85061062236&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061062236&partnerID=8YFLogxK

U2 - 10.5937/fmet1901166K

DO - 10.5937/fmet1901166K

M3 - Article

VL - 47

SP - 166

EP - 176

JO - FME Transactions

JF - FME Transactions

SN - 1451-2092

IS - 1

ER -