Journal of Advanced Marine Engineering and Technology

  • 제28권5호
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  • Pages.801-810
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  • 2004
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  • 2234-7925(pISSN)
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  • 2234-8352(eISSN)
한국마린엔지니어링학회 (The Korean Society of Marine Engineering)
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PRIMAL-DUAL 내부점법에 관한 연구

A Study on Primal-Dual Interior-Point Method

  • 발행 : 2004.07.01
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초록

The Primal-Dual Interior-Point (PDIP) method is currently one of the fastest emerging topics in optimization. This method has become an effective solution algorithm for large scale nonlinear optimization problems. such as the electric Optimal Power Flow (OPF) and natural gas and electricity OPF. This study describes major theoretical developments of the PDIP method as well as practical issues related to implementation of the method. A simple quadratic problem with linear equality and inequality constraints

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참고문헌

  1. Linear and nonlinear programming Stephen G. Nash;Ariela Sofer
  2. Class notes for ECEN 5193 at Oklahoma State Power economics and regulation Thomas W. Gedra
  3. Primal-dual interior-point methods Stephen J. Wright
  4. PhD thesis, Oklahoma State University Optimal power flow with expected security costs Parnjit Damrongkulkamjorn
  5. Power generation, operation, and control Allen J. Wood;Bruce F. Wollenberg
  6. Master's thesis, University of Illinois at Urbana-Champaign Implementation of a Newton-based optimal power flow into a power system simulation environment James Danel Weber
  7. IEEE Trans. on Power Systems v.7 no.2 A fast algorithm for power system optimization problems using an interior point method K. Ponnambalam;V. H. Quintana;A. Vannelli
  8. IEEE Trans. on Power Systems v.9 no.2 A direct nonlinear predictor corrector primal-dual interior point algorithm for optimal power flows Yu-Chi Wu;Debs, A.S.;R. E. Marsten
  9. Combinatorica v.4 A new polynomialtime algorithm for linear programming N. Karmarkar
  10. PhD thesis, Oklahoma State University Natural gas and electricity optimal power flow Seungwon An
  11. PhD thesis, Oklahoma State University Expected-security-cost optimal power flow with small signal stability constraints John Condren