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Power System Voltage Stability Classification Using Interior Point Method Based Support Vector Machine(IPMSVM)

Song, Hwa-Chang    (Department of Electrical Engineering, Seoul Nat'l University of Technology   ); Dosano, Rodel D.    (School of Electronic and Information Eng., Kunsan Nat'l University   ); Lee, Byong-Jun    (School of Electrical Engineering, Korea University  );
  • 초록

    This paper present same thodology for the classification of power system voltage stability, the trajectory of which to instability is monotonic, using an interior point method based support vector machine(IPMSVM). The SVM based voltage stability classifier canp rovide real-time stability identification only using the local measurement data, without the topological information conventionally used.


  • 주제어

    classification .   interior point method .   local measurement .   voltagestability identification .   support vector machine.  

  • 참고문헌 (14)

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    9. D. Michie, D. J. Spiegelhalter and C. C. Taylor(eds.), Machine learning, neural and statistical classification, Online:http://www.amsta.leeds.ac.uk/charles/statlog/whole.pdf 
    10. R. O. Burnett Jr.and M. M. Butts, "Power system applications for phasor measurement units, " IEEE Computer Applications in Power, vol.7,no.1,pp.8?13, 1994 
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  • 이 논문을 인용한 문헌 (2)

    1. 2011. "" International journal of fuzzy logic and intelligent systems : IJFIS, 11(4): 247~253     
    2. 2013. "" International journal of fuzzy logic and intelligent systems : IJFIS, 13(3): 171~177     

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    2. 2009 "Synchro-Phasor 기반 전력계통 감시제어 기술" 전기의 세계 = The proceedings of KIEE 58 (8): 42~50    
    3. 2010 "Identification of Dynamic Load Model Parameters Using Particle Swarm Optimization" International journal of fuzzy logic and intelligent systems : IJFIS 10 (2): 128~133    
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    5. 2012 "Parameter Estimation for the Composite Load Model" Journal of international council on electrical engineering 2 (2): 215~218    
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