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      KCI등재 SCIE SCOPUS

      Feeder Reconfiguration Using Binary Coding Particle Swarm Optimization

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      https://www.riss.kr/link?id=A76603467

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This paper proposes an effective approach based on binary coding Particle Swarm Optimization (PSO) to identify the switching operation plan for feeder reconfiguration. The proposed method considers the advantages and disadvantages of existing particle swarm optimization method and redefined the operators of PSO algorithm to fit the application field of distribution systems. Shift operator is proposed to construct the binary coding particle swarm optimization for feeder reconfiguration. A typical distribution system of Taiwan Power Company is used in this paper to demonstrate the effectiveness of the proposed method. The test results show that the proposed method can apply to feeder reconfiguration problems more effectively and stably than existing method.
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      This paper proposes an effective approach based on binary coding Particle Swarm Optimization (PSO) to identify the switching operation plan for feeder reconfiguration. The proposed method considers the advantages and disadvantages of existing particle...

      This paper proposes an effective approach based on binary coding Particle Swarm Optimization (PSO) to identify the switching operation plan for feeder reconfiguration. The proposed method considers the advantages and disadvantages of existing particle swarm optimization method and redefined the operators of PSO algorithm to fit the application field of distribution systems. Shift operator is proposed to construct the binary coding particle swarm optimization for feeder reconfiguration. A typical distribution system of Taiwan Power Company is used in this paper to demonstrate the effectiveness of the proposed method. The test results show that the proposed method can apply to feeder reconfiguration problems more effectively and stably than existing method.

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      목차 (Table of Contents)

      • Abstract
      • 1. INTRODUCTION
      • 2. PROBLEM FORMULATION
      • 3. PROPOSE APPROACH
      • 4. SIMULATION RESULTS
      • Abstract
      • 1. INTRODUCTION
      • 2. PROBLEM FORMULATION
      • 3. PROPOSE APPROACH
      • 4. SIMULATION RESULTS
      • 5. CONCLUSIONS
      • REFERANCE
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      참고문헌 (Reference)

      1 Y. Liu, "Reconfiguration of network skeleton based on discrete particle-swarm optimization for black-start restoration" 2006

      2 J. Kennedy, "Particle swarm optimization" Proc. IEEE Int’l. Conf. on Neural Networks 1942-1948, 1995

      3 M. E. Baran, "Network reconfiguration in distribution systems for loss reduction and load balancing" 4 (4): 1401-1407, 1989

      4 H. C. Chang, "Network reconfiguration in distribution system using simulated annealing" 29 : 227-238, 1994

      5 Y. T. Hsiao, "Mutiobjective evolution programming meth" 19 (19): 594-599, 2004

      6 K. Nara, "Implementation of genetic algorithm for distribution systems loss minimum re-configuration" 7 (7): 1044-1051, 1992

      7 R. C. Eberhart, "Comparison between genetic algorithms and particle swarm optimiza-tion" 1998

      8 H. Kim, "Artificial neural networks based feeder reconfiguration for loss reduction in distribution systems" 8 (8): 1356-1366, 1993

      9 E. Carpaneto, "Ant-colony search-based minimum losses reconfiguration of distribution systems" 971-974, 2004

      10 T. Q. D. Khoa, "Ant colony search based loss minimum for reconfiguration of distribution systems" 6-, 2006

      1 Y. Liu, "Reconfiguration of network skeleton based on discrete particle-swarm optimization for black-start restoration" 2006

      2 J. Kennedy, "Particle swarm optimization" Proc. IEEE Int’l. Conf. on Neural Networks 1942-1948, 1995

      3 M. E. Baran, "Network reconfiguration in distribution systems for loss reduction and load balancing" 4 (4): 1401-1407, 1989

      4 H. C. Chang, "Network reconfiguration in distribution system using simulated annealing" 29 : 227-238, 1994

      5 Y. T. Hsiao, "Mutiobjective evolution programming meth" 19 (19): 594-599, 2004

      6 K. Nara, "Implementation of genetic algorithm for distribution systems loss minimum re-configuration" 7 (7): 1044-1051, 1992

      7 R. C. Eberhart, "Comparison between genetic algorithms and particle swarm optimiza-tion" 1998

      8 H. Kim, "Artificial neural networks based feeder reconfiguration for loss reduction in distribution systems" 8 (8): 1356-1366, 1993

      9 E. Carpaneto, "Ant-colony search-based minimum losses reconfiguration of distribution systems" 971-974, 2004

      10 T. Q. D. Khoa, "Ant colony search based loss minimum for reconfiguration of distribution systems" 6-, 2006

      11 M. Kitayama, "An optimization method for distribution system configuration based on genetic algorithm" 614-619, 1995

      12 J.-H. Teng, "A novel ACS-based optimum switch relocation method" 18 (18): 113-120, 2003

      13 F.-Y. Hsu, "A multi-objective evolution programming method for feeder reconfiguration of power distribution system" 55-60, 2005

      14 Y. Shi, "A modified particle swarm optimizer" 69-73, 1998

      15 R. C. Eberhart, "A discrete binary version of the particle swarm algorithm" 4104-4108, 1997

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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
      2009-12-29 학회명변경 한글명 : 제어ㆍ로봇ㆍ시스템학회 -> 제어·로봇·시스템학회 KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-10-29 학회명변경 한글명 : 제어ㆍ자동화ㆍ시스템공학회 -> 제어ㆍ로봇ㆍ시스템학회
      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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