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      KCI등재 SCIE SCOPUS

      A Simultaneous Perturbation Stochastic Approximation (SPSA)-Based Model Approximation and its Application for Power System Stabilizers

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      https://www.riss.kr/link?id=A76603655

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This paper presents an intelligent model; named as free model, approach for a closed¬loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.
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      This paper presents an intelligent model; named as free model, approach for a closed¬loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alt...

      This paper presents an intelligent model; named as free model, approach for a closed¬loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

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      목차 (Table of Contents)

      • Abstract
      • 1. INTRODUCTION
      • 2. DESCRIPTION OF THE FREE MODEL
      • 3. SPSA BASED FREE MODEL APPROXIMATION
      • 4. STATE SPACE REALIZATION AND LQR DESIGN
      • Abstract
      • 1. INTRODUCTION
      • 2. DESCRIPTION OF THE FREE MODEL
      • 3. SPSA BASED FREE MODEL APPROXIMATION
      • 4. STATE SPACE REALIZATION AND LQR DESIGN
      • 5. COMPUTER SIMULATIONS
      • 6. CONCLUSION
      • APPENDIX
      • REFERENCES
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      참고문헌 (Reference)

      1 T. L. Hwang, "Two-level optimal output feedback stabilizer design" 6 (6): 1042-1047, 1991

      2 K. T. Law, "Robust controller structure for coordinate power system voltage regulator and stabilizer design" 2 (2): 220-232, 1994

      3 Rahmat-Allah Hooshmand, "Real-Coded Genetic Algorithm Based Design and Analysis of an Auto-Tuning Fuzzy Logic PSS" 대한전기학회 2 (2): 178-187, 2007

      4 A. Ghosh, "Power system stabilizer based on adaptive control techniques" 103 : 1983-1989, 1984

      5 K. Y. Lee, "Power system stabilization using free-model based inverse dynamic neuro controller" 2132-2137, 2002

      6 P. M. Anderson, "Power Systems Control and stability" Iowa State University Press 1984

      7 P. W. Sauer, "Power System Dynamics and Stability" Prentice Hall 1998

      8 J. C. Spall, "Multivariate stochastic approxi-mation using a simultaneous perturbation gradient approximation" 37 : 332-341, 1992

      9 B. D. O. Anderson, "Linear Optimal Control" Prentice Hall 1990

      10 J. C. Spall, "Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control" Wiley 2003

      1 T. L. Hwang, "Two-level optimal output feedback stabilizer design" 6 (6): 1042-1047, 1991

      2 K. T. Law, "Robust controller structure for coordinate power system voltage regulator and stabilizer design" 2 (2): 220-232, 1994

      3 Rahmat-Allah Hooshmand, "Real-Coded Genetic Algorithm Based Design and Analysis of an Auto-Tuning Fuzzy Logic PSS" 대한전기학회 2 (2): 178-187, 2007

      4 A. Ghosh, "Power system stabilizer based on adaptive control techniques" 103 : 1983-1989, 1984

      5 K. Y. Lee, "Power system stabilization using free-model based inverse dynamic neuro controller" 2132-2137, 2002

      6 P. M. Anderson, "Power Systems Control and stability" Iowa State University Press 1984

      7 P. W. Sauer, "Power System Dynamics and Stability" Prentice Hall 1998

      8 J. C. Spall, "Multivariate stochastic approxi-mation using a simultaneous perturbation gradient approximation" 37 : 332-341, 1992

      9 B. D. O. Anderson, "Linear Optimal Control" Prentice Hall 1990

      10 J. C. Spall, "Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control" Wiley 2003

      11 K. A. El-Metwally, "Fuzzy logic power system stabilizer" 143 (143): 263-268, 1996

      12 K. Ogata, "Discrete-Time Control System" Prentice Hall 1995

      13 C. L. Phillips, "Digital Control System Analysis and Design" Prentice Hall 1997

      14 Y. Y. Hsu, "Design of fuzzy power system stabilizers for multi-machine power systems" 137 (137): 233-238, 1990

      15 Sang-Seung Lee, "Damping Analysis using IEEEST PSS and PSS2A PSS" 대한전기학회 1 (1): 271-278, 2006

      16 S. A. Doi, "Coordinated synthesis of power system stabilizers in multimachine power systems" 103 : 1473-1479, 1984

      17 F. P. deMello, "Concept of synchronous machine stability as affected by excitation control" 103 : 316-319, 1969

      18 M. A. Pai, "Application of interval matrices in power system stabilizer design" 19 (19): 179-184, 1997

      19 Y. Zhang, "Application of an inverse input/output mapped ANN as a power system stabilizer" 9 (9): 433-441, 1994

      20 O. P. Malik, "An adaptive optimal controller and its application to an electric generating unit" 15 : 169-178, 1993

      21 W. Gu, "A self-tuning power system stabilizer for wide-range synchronous generator operation" 4 (4): 1191-1199, 1989

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
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      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
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      영문명 : The Institute Of Control, Automation, And Systems Engineers, Korea -> Institute of Control, Robotics and Systems
      KCI등재
      2005-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2004-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2002-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.35 0.6 1.07
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.88 0.73 0.388 0.04
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