• DocumentCode
    2638612
  • Title

    Particle swarm optimization for economic dispatch with line flow and voltage constraints [power generation scheduling]

  • Author

    Pancholi, Rohit Kumar ; Swarup, K. Shanti

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol., Chennai, India
  • Volume
    1
  • fYear
    2003
  • fDate
    15-17 Oct. 2003
  • Firstpage
    450
  • Abstract
    This paper presents an efficient and reliable evolutionary based approach to solve the economic load dispatch (ELD) with lineflows and voltage constraints The proposed approach employ a particle swarm optimization (PSO) algorithm for ELD. The incorporation of a type 1 PSO, as a derivative-free optimization technique in solving ELD with voltages and lineflow constraints, significantly relieves the assumptions imposed on the optimized objective function. The proposed approach has been tested on three representative systems, i.e. IEEE 14 bus, IEEE 30 bus and IEEE 57 bus systems respectively. The feasibility of the proposed method is demonstrated and the results are compared with linear programming, quadratic programming and genetic algorithms respectively. The developed algorithms are computationally faster than the other methods.
  • Keywords
    optimisation; power generation dispatch; power generation economics; power generation scheduling; ELD; IEEE 14 bus; IEEE 30 bus; IEEE 57 bus systems; economic load dispatch; evolutionary based method; genetic algorithm; line flow constraints; linear programming; optimized objective function; particle swarm optimization; power generation scheduling optimization; quadratic programming; type 1 PSO; voltage constraints; Constraint optimization; Genetic algorithms; Linear programming; Particle swarm optimization; Power generation; Power generation economics; Power system economics; Quadratic programming; System testing; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2003. Conference on Convergent Technologies for the Asia-Pacific Region
  • Print_ISBN
    0-7803-8162-9
  • Type

    conf

  • DOI
    10.1109/TENCON.2003.1273363
  • Filename
    1273363