Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine Networks

Mohammad Saiful Islam; Md Rashidul Islam; Md Shafiullah; Md Samiul Azam

doi:10.1109/ICAEEE54957.2022.9836405

Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine Networks

Mohammad Saiful Islam
, Md Rashidul Islam
, Md Shafiullah
, Md Samiul Azam

Interdisciplinary Research Center for Sustainable Energy Systems

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

2 Scopus citations

Abstract

Low-frequency oscillation (LFO) is a significant problem for Multi-machine power system (MPS) networks. It makes the power system networks unstable. In this article, a new Power system stabilizer (PSS) design method is demonstrated using the Dragonfly algorithm (DA). To enhance system damping, a damping ratio-based objective function is used, and a typical lead-lag type PSS (CPSS) structure is considered. In this case, the algorithm's ability to provide the best PSS design regardless of the starting guess demonstrates its robustness. This method is tested on two separate multi-machine networks exposed to a 3-F fault, and compared with two well-known optimization algorithms called PSO and BSA. The optimization results show that the DA technique provides better system damping than PSO and BSA.

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/ICAEEE54957.2022.9836405
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

DA
Damping Ratio
Meta-heuristics techniques
Multi-machines network
PSO
PSS

ASJC Scopus subject areas

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

Access to Document

10.1109/ICAEEE54957.2022.9836405

Cite this

Islam, M. S., Islam, M. R., Shafiullah, M., & Azam, M. S. (2022). Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine 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/ICAEEE54957.2022.9836405

Islam, Mohammad Saiful ; Islam, Md Rashidul ; Shafiullah, Md et al. / Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine 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).

@inproceedings{4246429be61140089a10a1dd4d17cd69,

title = "Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine Networks",

abstract = "Low-frequency oscillation (LFO) is a significant problem for Multi-machine power system (MPS) networks. It makes the power system networks unstable. In this article, a new Power system stabilizer (PSS) design method is demonstrated using the Dragonfly algorithm (DA). To enhance system damping, a damping ratio-based objective function is used, and a typical lead-lag type PSS (CPSS) structure is considered. In this case, the algorithm's ability to provide the best PSS design regardless of the starting guess demonstrates its robustness. This method is tested on two separate multi-machine networks exposed to a 3-F fault, and compared with two well-known optimization algorithms called PSO and BSA. The optimization results show that the DA technique provides better system damping than PSO and BSA.",

keywords = "DA, Damping Ratio, Meta-heuristics techniques, Multi-machines network, PSO, PSS",

author = "Islam, \{Mohammad Saiful\} and Islam, \{Md Rashidul\} and Md Shafiullah and Azam, \{Md Samiul\}",

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

year = "2022",

doi = "10.1109/ICAEEE54957.2022.9836405",

language = "English",

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

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

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

address = "United States",

}

Islam, MS, Islam, MR, Shafiullah, M & Azam, MS 2022, Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine 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/ICAEEE54957.2022.9836405

Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine Networks. / Islam, Mohammad Saiful; 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 - Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine Networks

AU - Islam, Mohammad Saiful

AU - Islam, Md Rashidul

AU - Shafiullah, Md

AU - Azam, Md Samiul

PY - 2022

Y1 - 2022

N2 - Low-frequency oscillation (LFO) is a significant problem for Multi-machine power system (MPS) networks. It makes the power system networks unstable. In this article, a new Power system stabilizer (PSS) design method is demonstrated using the Dragonfly algorithm (DA). To enhance system damping, a damping ratio-based objective function is used, and a typical lead-lag type PSS (CPSS) structure is considered. In this case, the algorithm's ability to provide the best PSS design regardless of the starting guess demonstrates its robustness. This method is tested on two separate multi-machine networks exposed to a 3-F fault, and compared with two well-known optimization algorithms called PSO and BSA. The optimization results show that the DA technique provides better system damping than PSO and BSA.

AB - Low-frequency oscillation (LFO) is a significant problem for Multi-machine power system (MPS) networks. It makes the power system networks unstable. In this article, a new Power system stabilizer (PSS) design method is demonstrated using the Dragonfly algorithm (DA). To enhance system damping, a damping ratio-based objective function is used, and a typical lead-lag type PSS (CPSS) structure is considered. In this case, the algorithm's ability to provide the best PSS design regardless of the starting guess demonstrates its robustness. This method is tested on two separate multi-machine networks exposed to a 3-F fault, and compared with two well-known optimization algorithms called PSO and BSA. The optimization results show that the DA technique provides better system damping than PSO and BSA.

KW - DA

KW - Damping Ratio

KW - Meta-heuristics techniques

KW - Multi-machines network

KW - PSO

KW - PSS

UR - https://www.scopus.com/pages/publications/85136216941

U2 - 10.1109/ICAEEE54957.2022.9836405

DO - 10.1109/ICAEEE54957.2022.9836405

M3 - Conference contribution

AN - SCOPUS:85136216941

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 -

Islam MS, Islam MR, Shafiullah M, Azam MS. Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine 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/ICAEEE54957.2022.9836405

Dragonfly Algorithm for Robust Tuning of Power System Stabilizers in Multimachine Networks

Abstract

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Bibliographical note

Keywords

ASJC Scopus subject areas

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