BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Algorithms; Circuit oscillations; Controllers; Ecology; Electric control equipment; Electric power system control; Heuristic algorithms; MATLAB; Optimization; Particle swarm optimization (PSO); Power control; Synchronous machinery; Three term control systems; Tuning; Two term control systems; Adapta...
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Turkiye Klinikleri Journal of Medical Sciences
2023
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my.uniten.dspace-229632023-05-29T14:13:46Z BBO algorithm-based tuning of PID controller for speed control of synchronous machine Kasilingam G. Pasupuleti J. 55812078500 11340187300 Algorithms; Circuit oscillations; Controllers; Ecology; Electric control equipment; Electric power system control; Heuristic algorithms; MATLAB; Optimization; Particle swarm optimization (PSO); Power control; Synchronous machinery; Three term control systems; Tuning; Two term control systems; Adaptation law; Biogeography-based optimization algorithms; Biogeographybased optimizations (BBO); Electromechanical oscilla-tions; PID controllers; Power System Stabilizer; Proportional integral derivative controllers; Single machine infinite bus system; Proportional control systems A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance. � 2016 T�bitak. Final 2023-05-29T06:13:46Z 2023-05-29T06:13:46Z 2016 Article 10.3906/elk-1501-46 2-s2.0-84974698198 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974698198&doi=10.3906%2felk-1501-46&partnerID=40&md5=5a6fbd5e42b72e34528f6e1d8fbc7679 https://irepository.uniten.edu.my/handle/123456789/22963 24 4 3274 3285 Turkiye Klinikleri Journal of Medical Sciences Scopus |
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Algorithms; Circuit oscillations; Controllers; Ecology; Electric control equipment; Electric power system control; Heuristic algorithms; MATLAB; Optimization; Particle swarm optimization (PSO); Power control; Synchronous machinery; Three term control systems; Tuning; Two term control systems; Adaptation law; Biogeography-based optimization algorithms; Biogeographybased optimizations (BBO); Electromechanical oscilla-tions; PID controllers; Power System Stabilizer; Proportional integral derivative controllers; Single machine infinite bus system; Proportional control systems |
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55812078500 Kasilingam G. Pasupuleti J. |
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Kasilingam G. Pasupuleti J. |
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Kasilingam G. Pasupuleti J. BBO algorithm-based tuning of PID controller for speed control of synchronous machine |
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Kasilingam G. |
title |
BBO algorithm-based tuning of PID controller for speed control of synchronous machine |
title_short |
BBO algorithm-based tuning of PID controller for speed control of synchronous machine |
title_full |
BBO algorithm-based tuning of PID controller for speed control of synchronous machine |
title_fullStr |
BBO algorithm-based tuning of PID controller for speed control of synchronous machine |
title_full_unstemmed |
BBO algorithm-based tuning of PID controller for speed control of synchronous machine |
title_sort |
bbo algorithm-based tuning of pid controller for speed control of synchronous machine |
publisher |
Turkiye Klinikleri Journal of Medical Sciences |
publishDate |
2023 |
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1806425592231362560 |
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13.222552 |