• DocumentCode
    2385480
  • Title

    A enhanced multiple predictor-corrector interior point method for optimal power flow

  • Author

    Xie, Liang ; Chiang, Hsiao-Dong

  • Author_Institution
    Sch. of Electron., Inf. & Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2010
  • fDate
    25-29 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Interior point method (IPM), as one of the most efficient methods, is being extended to solve different types of optimization problems in electric power domain. In this paper, the nonlinear OPF problem, formulated with a rectangular coordinate form, is solved using the enhanced multiple predictor-corrector interior point method, which is combined with the selection of the optimal composite direction. An two stage linesearch strategy is also employed to obtain an optimal composite direction to improve the convergence property of MPC. The proposed method is then simulated for several test system ranging in size from 57 buses to 2790 buses. Numerical results demonstrate that the proposed method can lead to convergence with a smaller number of iterations and better computational time. Moreover, the comparison with different methods shows that the proposed method can be faster and robuster than that traditional predictor-corrector interior point method and its variant.
  • Keywords
    load flow; optimisation; predictor-corrector methods; convergence property; enhanced multiple predictor-corrector interior point method; interior point method; nonlinear OPF problem; optimal composite direction; optimal power flow; optimization problems; Interior point method; Line search; Nonlinear Programming; Optimal power flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2010 IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4244-6549-1
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PES.2010.5589934
  • Filename
    5589934