• DocumentCode
    2102718
  • Title

    Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization

  • Author

    Wang, Shouzheng ; Ma, Lixin ; Sun, Dashuai

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
  • fYear
    2010
  • fDate
    28-31 March 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms´. It is shown that the approach developed is feasible and efficient.
  • Keywords
    evolutionary computation; minimisation; particle swarm optimisation; reactive power; IEEE 14-bus system; hybrid differential evolution particle swarm optimization algorithm; metaheuristic techniques; mixed integer nonlinear programming; nonlinear optimization; power system voltage; reactive power optimization; system loss minimization; Hybrid power systems; Linear programming; Niobium; Particle swarm optimization; Power generation; Power system simulation; Quadratic programming; Reactive power; Sun; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-4812-8
  • Electronic_ISBN
    978-1-4244-4813-5
  • Type

    conf

  • DOI
    10.1109/APPEEC.2010.5448803
  • Filename
    5448803