• DocumentCode
    589839
  • Title

    A new Hybrid Fuzzy Dynamic Velocity Feedback PSO for non-convex economic dispatch problem

  • Author

    Muneender, E. ; Vinodkumar, D.M.

  • Author_Institution
    Electr. Eng. Dept., KU Coll. of Eng. & Technol., Warangal, India
  • fYear
    2012
  • fDate
    6-9 Oct. 2012
  • Firstpage
    145
  • Lastpage
    150
  • Abstract
    This paper proposes a new Hybrid Fuzzy Dynamic Velocity Feedback Particle Swarm Optimization (HFDVF-PSO) for solving Economic Dispatch (ED) problem with non-smooth cost functions considering valve-point effects and multiple fuel options. In the proposed HFDVF-PSO method, the inertia weight is dynamically and nonlinearly adjusted to obtain better balance between global and local search abilities of the PSO using the absolute value of the average velocity of the particles as a feedback to the fuzzy inference system. The performance of the proposed method is tested on standard 10-unit test system and is compared with the conventional PSO method and the methods reported in literature. The simulation results reveal that the proposed HFDVF-PSO method out performs the conventional PSO and other Evolutionary Algorithms (EA) reported in literature.
  • Keywords
    concave programming; fuzzy reasoning; particle swarm optimisation; power generation dispatch; power generation economics; search problems; ED problem; HFDVF-PSO method; dynamic adjustment; fuel options; fuzzy inference system; global search ability; hybrid fuzzy dynamic velocity feedback PSO; inertia weight; local search ability; nonconvex economic dispatch problem; nonlinear adjustment; nonsmooth cost functions; particle swarm optimization; standard 10-unit test system; valve-point effects; Fuels; Heuristic algorithms; Loading; Optimization; Particle swarm optimization; Standards; Valves; Artificial Intelligence; Economic Dispatch; Particle Swarm Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sustainable Utilization and Development in Engineering and Technology (STUDENT), 2012 IEEE Conference on
  • Conference_Location
    Kuala Lumpur
  • ISSN
    1985-5753
  • Print_ISBN
    978-1-4673-1649-1
  • Electronic_ISBN
    1985-5753
  • Type

    conf

  • DOI
    10.1109/STUDENT.2012.6408386
  • Filename
    6408386