Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer

To improve the capacity of the power system damping, a power system stabilizers (PSSs) is typically the chosen option. Traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but th...

Full description

Bibliographic Details
Main Authors: Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi
Format: Conference or Workshop Item
Published: IEEE 2022
Online Access:http://psasir.upm.edu.my/id/eprint/37791/
_version_ 1848848701307486208
author Sabo, Aliyu
Abdul Wahab, Noor Izzri
Othman, Mohammad Lutfi
author_facet Sabo, Aliyu
Abdul Wahab, Noor Izzri
Othman, Mohammad Lutfi
author_sort Sabo, Aliyu
building UPM Institutional Repository
collection Online Access
description To improve the capacity of the power system damping, a power system stabilizers (PSSs) is typically the chosen option. Traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but they are both difficult and expensive. Implementing a PSSs damping controller requires extensive system modeling, placing a heavy computational burden on the system, and is a time-consuming process. A Neuro-Fuzzy Controller (NFC), a damping controller that can take the place of the FFA-PSS controller, was proposed to address these shortcomings. The dynamic model of 10-machine test systems under multiple operating conditions was developed with the presence of NFC in SIMULINK. After carrying out the time-domain simulation on the New England IEEE test system, the proposed NFC model produced a 13% rotor speed and 43% rotor angle respective angle stability enhancement in G5 based on the time to settle when compared to the FFA-PSS model. Our work has led us to conclude that the simulation results with the proposed NFC model shows that the Electromechanical Modes (EMs) eigenvalues were shifted to the left in S-plane and the system damping was greatly enhanced.
first_indexed 2025-11-15T09:38:41Z
format Conference or Workshop Item
id upm-37791
institution Universiti Putra Malaysia
institution_category Local University
last_indexed 2025-11-15T09:38:41Z
publishDate 2022
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling upm-377912023-11-06T10:17:45Z http://psasir.upm.edu.my/id/eprint/37791/ Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer Sabo, Aliyu Abdul Wahab, Noor Izzri Othman, Mohammad Lutfi To improve the capacity of the power system damping, a power system stabilizers (PSSs) is typically the chosen option. Traditional PSSs performance fails to provide superior damping under other operating circumstances. Many adaptive control approaches have been proposed to solve this problem, but they are both difficult and expensive. Implementing a PSSs damping controller requires extensive system modeling, placing a heavy computational burden on the system, and is a time-consuming process. A Neuro-Fuzzy Controller (NFC), a damping controller that can take the place of the FFA-PSS controller, was proposed to address these shortcomings. The dynamic model of 10-machine test systems under multiple operating conditions was developed with the presence of NFC in SIMULINK. After carrying out the time-domain simulation on the New England IEEE test system, the proposed NFC model produced a 13% rotor speed and 43% rotor angle respective angle stability enhancement in G5 based on the time to settle when compared to the FFA-PSS model. Our work has led us to conclude that the simulation results with the proposed NFC model shows that the Electromechanical Modes (EMs) eigenvalues were shifted to the left in S-plane and the system damping was greatly enhanced. IEEE 2022 Conference or Workshop Item PeerReviewed Sabo, Aliyu and Abdul Wahab, Noor Izzri and Othman, Mohammad Lutfi (2022) Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer. In: 2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES 2022), 9-12 Dec. 2022, Beijing, China. (pp. 1506-1511). https://ieeexplore.ieee.org/document/10082239 10.1109/SPIES55999.2022.10082239
spellingShingle Sabo, Aliyu
Abdul Wahab, Noor Izzri
Othman, Mohammad Lutfi
Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
title Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
title_full Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
title_fullStr Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
title_full_unstemmed Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
title_short Optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
title_sort optimal design of multi-machine power system damping controller using neuro-fuzzy controller based stabilizer
url http://psasir.upm.edu.my/id/eprint/37791/
http://psasir.upm.edu.my/id/eprint/37791/
http://psasir.upm.edu.my/id/eprint/37791/