Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks

Sayed Md Abrar Gani; Md Rashidul Islam; Md Shafiullah; Jahid Hasan Tayeb; Md Ismail Hossain; Amjad Ali

doi:10.1109/ICAEEE54957.2022.9836358

Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks

Sayed Md Abrar Gani
, Md Rashidul Islam
, Md Shafiullah
, Jahid Hasan Tayeb
, Md Ismail Hossain
, Amjad Ali

Interdisciplinary Research Center for Sustainable Energy Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

An evolutionary algorithm-based power system stabilizers (PSS) design for low-frequency oscillations (LFO) damping in multi-machine power system networks (MMPSNs) is presented in this paper. A damping ratio-based objective function is developed to enhance the system damping where the widely employed lead-lag type PSS is considered in the problem formulation. The equilibrium Optimizer (EO), a recently developed metaheuristic algorithm that is capable of finding optimal solutions in complex engineering problems, is employed in this article. The algorithm's resilience is demonstrated by its ability to lead to the best PSS design regardless of the initial assumption made by the user. Two distinct multi-machine networks 2-area 4-machine and IEEE 10-machine 39-bus are used in this research. EO-based PSS results are compared with traditional PSS results to investigate which one yields better results for stability. According to the simulation findings, the EO technique reduces the settling time and overshoot significantly over the other techniques.

Original language	English
Title of host publication	2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665469449
DOIs	https://doi.org/10.1109/ICAEEE54957.2022.9836358
State	Published - 2022

Publication series

Name	2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Damping ratio
EO
Eigenvalues
Metaheuristic
Multi-machine network
PSS

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Electrical and Electronic Engineering
Instrumentation

Access to Document

10.1109/ICAEEE54957.2022.9836358

Cite this

Gani, S. M. A., Islam, M. R., Shafiullah, M., Tayeb, J. H., Hossain, M. I., & Ali, A. (2022). Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks. In 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022 (2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAEEE54957.2022.9836358

Gani, Sayed Md Abrar ; Islam, Md Rashidul ; Shafiullah, Md et al. / Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks. 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022).

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title = "Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks",

abstract = "An evolutionary algorithm-based power system stabilizers (PSS) design for low-frequency oscillations (LFO) damping in multi-machine power system networks (MMPSNs) is presented in this paper. A damping ratio-based objective function is developed to enhance the system damping where the widely employed lead-lag type PSS is considered in the problem formulation. The equilibrium Optimizer (EO), a recently developed metaheuristic algorithm that is capable of finding optimal solutions in complex engineering problems, is employed in this article. The algorithm's resilience is demonstrated by its ability to lead to the best PSS design regardless of the initial assumption made by the user. Two distinct multi-machine networks 2-area 4-machine and IEEE 10-machine 39-bus are used in this research. EO-based PSS results are compared with traditional PSS results to investigate which one yields better results for stability. According to the simulation findings, the EO technique reduces the settling time and overshoot significantly over the other techniques.",

keywords = "Damping ratio, EO, Eigenvalues, Metaheuristic, Multi-machine network, PSS",

author = "Gani, \{Sayed Md Abrar\} and Islam, \{Md Rashidul\} and Md Shafiullah and Tayeb, \{Jahid Hasan\} and Hossain, \{Md Ismail\} and Amjad Ali",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.",

year = "2022",

doi = "10.1109/ICAEEE54957.2022.9836358",

language = "English",

series = "2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

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Gani, SMA, Islam, MR, Shafiullah, M, Tayeb, JH, Hossain, MI & Ali, A 2022, Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks. in 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022. 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICAEEE54957.2022.9836358

Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks. / Gani, Sayed Md Abrar; Islam, Md Rashidul; Shafiullah, Md et al.
2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks

AU - Gani, Sayed Md Abrar

AU - Islam, Md Rashidul

AU - Shafiullah, Md

AU - Tayeb, Jahid Hasan

AU - Hossain, Md Ismail

AU - Ali, Amjad

PY - 2022

Y1 - 2022

N2 - An evolutionary algorithm-based power system stabilizers (PSS) design for low-frequency oscillations (LFO) damping in multi-machine power system networks (MMPSNs) is presented in this paper. A damping ratio-based objective function is developed to enhance the system damping where the widely employed lead-lag type PSS is considered in the problem formulation. The equilibrium Optimizer (EO), a recently developed metaheuristic algorithm that is capable of finding optimal solutions in complex engineering problems, is employed in this article. The algorithm's resilience is demonstrated by its ability to lead to the best PSS design regardless of the initial assumption made by the user. Two distinct multi-machine networks 2-area 4-machine and IEEE 10-machine 39-bus are used in this research. EO-based PSS results are compared with traditional PSS results to investigate which one yields better results for stability. According to the simulation findings, the EO technique reduces the settling time and overshoot significantly over the other techniques.

AB - An evolutionary algorithm-based power system stabilizers (PSS) design for low-frequency oscillations (LFO) damping in multi-machine power system networks (MMPSNs) is presented in this paper. A damping ratio-based objective function is developed to enhance the system damping where the widely employed lead-lag type PSS is considered in the problem formulation. The equilibrium Optimizer (EO), a recently developed metaheuristic algorithm that is capable of finding optimal solutions in complex engineering problems, is employed in this article. The algorithm's resilience is demonstrated by its ability to lead to the best PSS design regardless of the initial assumption made by the user. Two distinct multi-machine networks 2-area 4-machine and IEEE 10-machine 39-bus are used in this research. EO-based PSS results are compared with traditional PSS results to investigate which one yields better results for stability. According to the simulation findings, the EO technique reduces the settling time and overshoot significantly over the other techniques.

KW - Damping ratio

KW - EO

KW - Eigenvalues

KW - Metaheuristic

KW - Multi-machine network

KW - PSS

UR - https://www.scopus.com/pages/publications/85136174525

U2 - 10.1109/ICAEEE54957.2022.9836358

DO - 10.1109/ICAEEE54957.2022.9836358

M3 - Conference contribution

AN - SCOPUS:85136174525

T3 - 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022

BT - 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Gani SMA, Islam MR, Shafiullah M, Tayeb JH, Hossain MI , Ali A. Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks. In 2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (2022 International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2022). doi: 10.1109/ICAEEE54957.2022.9836358

Equilibrium Optimizer for LFO Damping in Multimachine Power System Networks

Abstract

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Bibliographical note

Keywords

ASJC Scopus subject areas

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