• DocumentCode
    1065644
  • Title

    A hybrid genetic algorithm-interior point method for optimal reactive power flow

  • Author

    Yan, Wei ; Liu, Fang ; Chung, C.Y. ; Wong, K.P.

  • Author_Institution
    Minist. of Educ., Key Lab. of High Voltage Eng. & Electr. New Technol., Chongqing
  • Volume
    21
  • Issue
    3
  • fYear
    2006
  • Firstpage
    1163
  • Lastpage
    1169
  • Abstract
    By integrating a genetic algorithm (GA) with a nonlinear interior point method (IPM), a novel hybrid method for the optimal reactive power flow (ORPF) problem is proposed in this paper. The proposed method can be mainly divided into two parts. The first part is to solve the ORPF with the IPM by relaxing the discrete variables. The second part is to decompose the original ORPF into two sub-problems: continuous optimization and discrete optimization. The GA is used to solve the discrete optimization with the continuous variables being fixed, whereas the IPM solves the continuous optimization with the discrete variables being constant. The optimal solution can be obtained by solving the two sub-problems alternately. A dynamic adjustment strategy is also proposed to make the GA and the IPM to complement each other and to enhance the efficiency of the hybrid proposed method. Numerical simulations on the IEEE 30-bus, IEEE 118-bus and Chongqing 161-bus test systems illustrate that the proposed hybrid method is efficient for the ORPF problem
  • Keywords
    genetic algorithms; load flow; Chongqing 161-bus test systems; IEEE 118-bus test systems; IEEE 30-bus test systems; continuous optimization; discrete optimization; dynamic adjustment strategy; hybrid genetic algorithm; nonlinear interior point method; optimal reactive power flow; Genetic algorithms; Helium; Laboratories; Numerical simulation; Power generation; Programming profession; Reactive power; System testing; Transformers; Voltage control; Genetic algorithm (GA); interior point method (IPM); nonlinear programming; optimal reactive power flow (ORPF);
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2006.879262
  • Filename
    1664951