• DocumentCode
    2854374
  • Title

    A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation

  • Author

    Chen, Hou-he ; Li, Guo-qing ; Liao, Hai-liang

  • Author_Institution
    North China Electr. Power Univ., Beijing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    200
  • Lastpage
    205
  • Abstract
    A self-adaptive improved particle swarm optimization (IPSO) algorithm applied to available transfer capability (ATC) calculation is presented in this paper. Firstly, a new self-adaptive adjustment inertia-weighted strategy factor, which elevates the adaptability of particle swarm optimization (PSO) and accelerates convergence-speed of PSO, is proposed. Secondly, studying the search characteristics of PSO, penalty function is assigned dynamically. By this enhanced study behavior, the opportunity to find the global optimum is increased and the influence of the initial position of the particles is decreased. Thirdly, IPSO algorithm is adopted to solve the problem of ATC calculation. At last, the numeric simulation for IEEE 30-bus system demonstrates that this new IPSO is feasible and effective to solve the problem of ATC calculation.
  • Keywords
    algorithm theory; particle swarm optimisation; self-adjusting systems; global optimum; numeric simulation; penalty function; self-adaptive adjustment inertia-weighted strategy factor; self-adaptive improved particle swarm optimization algorithm; transfer capability calculation; Acceleration; Computational modeling; Convergence; Evolutionary computation; Iterative algorithms; Load flow; Neural networks; Numerical simulation; Particle swarm optimization; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.214
  • Filename
    5365602