An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

Damping; Eigenvalues and eigenfunctions; Electric power systems; Learning algorithms; Optimization; Particle swarm optimization (PSO); Problem solving; State space methods; Test facilities; Backtracking search algorithms; Multi machine power system; Power system damping; Power system oscillations; P...

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Main Authors: Islam N.N., Hannan M.A., Shareef H., Mohamed A.
Other Authors: 56119162900
Format: Article
Published: Elsevier B.V. 2023
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spelling my.uniten.dspace-232292023-05-29T14:38:36Z An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system Islam N.N. Hannan M.A. Shareef H. Mohamed A. 56119162900 7103014445 57189691198 57195440511 Damping; Eigenvalues and eigenfunctions; Electric power systems; Learning algorithms; Optimization; Particle swarm optimization (PSO); Problem solving; State space methods; Test facilities; Backtracking search algorithms; Multi machine power system; Power system damping; Power system oscillations; Power system stability; Power System Stabilizer; System stability; algorithm; Article; backtracking search algorithm; bacterial foraging optimization algorithm; machine; mathematical analysis; mathematical computing; mathematical parameters; particle swarm optimization; power supply; power system stabilizer; process optimization; statistical model This paper deals with the backtracking search algorithm (BSA) optimization technique to solve the design problems of multi-machine power system stabilizers (PSSs) in large power system. Power system stability problem is formulated by an optimization problem using the LTI state space model of the power system. To conduct a comprehensive analysis, two test systems (2-AREA and 5-AREA) are considered to explain the variation of design performance with increase in system size. Additionally, two metaheuristic algorithms, namely bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) are accounted to evaluate the overall design assessment. The obtained results show that BSA is superior to find consistent solution than BFOA and PSO regardless of system size. The damping performance that achieved from both test systems are sufficient to achieve fast system stability. System stability in linearized model is ensured in terms of eigenvalue shifting towards stability regions. On the other hand, damping performance in the non-linear model is evaluated in terms of overshoot and setting times. The obtained damping in both test systems are stable for BSA based design. However, BFOA and PSO based design perform worst in case of large power system. It is also found that the performance of BSA is not affected for large numbers of parameter optimization compared to PSO, and BFOA optimization techniques. This unique feature encourages recommending the developed backtracking search algorithm for PSS design of large multi-machine power system. � 2017 Final 2023-05-29T06:38:36Z 2023-05-29T06:38:36Z 2017 Article 10.1016/j.neucom.2016.10.022 2-s2.0-85008704831 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008704831&doi=10.1016%2fj.neucom.2016.10.022&partnerID=40&md5=c767fe8d76945e48f67ef699908d9c7b https://irepository.uniten.edu.my/handle/123456789/23229 237 175 184 Elsevier B.V. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Damping; Eigenvalues and eigenfunctions; Electric power systems; Learning algorithms; Optimization; Particle swarm optimization (PSO); Problem solving; State space methods; Test facilities; Backtracking search algorithms; Multi machine power system; Power system damping; Power system oscillations; Power system stability; Power System Stabilizer; System stability; algorithm; Article; backtracking search algorithm; bacterial foraging optimization algorithm; machine; mathematical analysis; mathematical computing; mathematical parameters; particle swarm optimization; power supply; power system stabilizer; process optimization; statistical model
author2 56119162900
author_facet 56119162900
Islam N.N.
Hannan M.A.
Shareef H.
Mohamed A.
format Article
author Islam N.N.
Hannan M.A.
Shareef H.
Mohamed A.
spellingShingle Islam N.N.
Hannan M.A.
Shareef H.
Mohamed A.
An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
author_sort Islam N.N.
title An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
title_short An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
title_full An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
title_fullStr An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
title_full_unstemmed An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
title_sort application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
publisher Elsevier B.V.
publishDate 2023
_version_ 1806427861970583552
score 13.188404