Parameter optimization of multimachine power system conventional stabilizers using CDCARLA method

M. Kashki; Y. L. Abdel-Magid; M. A. Abido

doi:10.1016/j.ijepes.2009.09.014

Parameter optimization of multimachine power system conventional stabilizers using CDCARLA method

M. Kashki^*, Y. L. Abdel-Magid, M. A. Abido

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

In this paper, a novel Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) based approach for optimal design of multimachine power system stabilizers (PSSs) is presented. The proposed CDCARLA based design approach is a combined procedure of two optimization stages in discrete and continuous spaces for fast convergence and high optimization efficiency. The potential of the proposed approach in seeking the optimal settings of the widely used conventional lead-lag PSSs' parameters is investigated and assessed in multimachine power systems. The performance and robustness of the proposed CDCARLA based PSS is evaluated under different power system disturbances. The performance of the proposed stabilizer is also compared with other stabilizers reported in the literature including the multi-band PSSs for a two-area four-machine power system. Simulation results show the effectiveness and robustness of the proposed CDCARLA PSS in damping local and inter area oscillation modes under various disturbances, and confirm its superiority in comparison with other types of PSSs.

Original language	English
Pages (from-to)	498-506
Number of pages	9
Journal	International Journal of Electrical Power and Energy Systems
Volume	32
Issue number	5
DOIs	https://doi.org/10.1016/j.ijepes.2009.09.014
State	Published - Jun 2010

Bibliographical note

Funding Information:
M. Kashki acknowledges the support of K-Sun Pars Consultants Engineering Co. which is a famous and good sound engineering company in the fields of Oil, Gas and Petrochemical. Dr. M. A. Abido would like to acknowledge the support of King Fahd University of Petroleum and Minerals via funded Project # IN090019 .

Keywords

Multimachine power system
Optimization
Power system stabilizer
Reinforcement learning automata

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1016/j.ijepes.2009.09.014

Cite this

@article{183bd5dffb844e328347014f323f9bde,

title = "Parameter optimization of multimachine power system conventional stabilizers using CDCARLA method",

abstract = "In this paper, a novel Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) based approach for optimal design of multimachine power system stabilizers (PSSs) is presented. The proposed CDCARLA based design approach is a combined procedure of two optimization stages in discrete and continuous spaces for fast convergence and high optimization efficiency. The potential of the proposed approach in seeking the optimal settings of the widely used conventional lead-lag PSSs' parameters is investigated and assessed in multimachine power systems. The performance and robustness of the proposed CDCARLA based PSS is evaluated under different power system disturbances. The performance of the proposed stabilizer is also compared with other stabilizers reported in the literature including the multi-band PSSs for a two-area four-machine power system. Simulation results show the effectiveness and robustness of the proposed CDCARLA PSS in damping local and inter area oscillation modes under various disturbances, and confirm its superiority in comparison with other types of PSSs.",

keywords = "Multimachine power system, Optimization, Power system stabilizer, Reinforcement learning automata",

author = "M. Kashki and Abdel-Magid, \{Y. L.\} and Abido, \{M. A.\}",

note = "Funding Information: M. Kashki acknowledges the support of K-Sun Pars Consultants Engineering Co. which is a famous and good sound engineering company in the fields of Oil, Gas and Petrochemical. Dr. M. A. Abido would like to acknowledge the support of King Fahd University of Petroleum and Minerals via funded Project \# IN090019 .",

year = "2010",

month = jun,

doi = "10.1016/j.ijepes.2009.09.014",

language = "English",

volume = "32",

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AU - Kashki, M.

AU - Abdel-Magid, Y. L.

AU - Abido, M. A.

N1 - Funding Information: M. Kashki acknowledges the support of K-Sun Pars Consultants Engineering Co. which is a famous and good sound engineering company in the fields of Oil, Gas and Petrochemical. Dr. M. A. Abido would like to acknowledge the support of King Fahd University of Petroleum and Minerals via funded Project # IN090019 .

PY - 2010/6

Y1 - 2010/6

N2 - In this paper, a novel Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) based approach for optimal design of multimachine power system stabilizers (PSSs) is presented. The proposed CDCARLA based design approach is a combined procedure of two optimization stages in discrete and continuous spaces for fast convergence and high optimization efficiency. The potential of the proposed approach in seeking the optimal settings of the widely used conventional lead-lag PSSs' parameters is investigated and assessed in multimachine power systems. The performance and robustness of the proposed CDCARLA based PSS is evaluated under different power system disturbances. The performance of the proposed stabilizer is also compared with other stabilizers reported in the literature including the multi-band PSSs for a two-area four-machine power system. Simulation results show the effectiveness and robustness of the proposed CDCARLA PSS in damping local and inter area oscillation modes under various disturbances, and confirm its superiority in comparison with other types of PSSs.

AB - In this paper, a novel Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) based approach for optimal design of multimachine power system stabilizers (PSSs) is presented. The proposed CDCARLA based design approach is a combined procedure of two optimization stages in discrete and continuous spaces for fast convergence and high optimization efficiency. The potential of the proposed approach in seeking the optimal settings of the widely used conventional lead-lag PSSs' parameters is investigated and assessed in multimachine power systems. The performance and robustness of the proposed CDCARLA based PSS is evaluated under different power system disturbances. The performance of the proposed stabilizer is also compared with other stabilizers reported in the literature including the multi-band PSSs for a two-area four-machine power system. Simulation results show the effectiveness and robustness of the proposed CDCARLA PSS in damping local and inter area oscillation modes under various disturbances, and confirm its superiority in comparison with other types of PSSs.

KW - Multimachine power system

KW - Optimization

KW - Power system stabilizer

KW - Reinforcement learning automata

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DO - 10.1016/j.ijepes.2009.09.014

M3 - Article

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SN - 0142-0615

VL - 32

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JO - International Journal of Electrical Power and Energy Systems

JF - International Journal of Electrical Power and Energy Systems

IS - 5

ER -

Parameter optimization of multimachine power system conventional stabilizers using CDCARLA method

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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