• DocumentCode
    1944182
  • Title

    Application of Multi Objective Evolutionary Programming to Combined Economic Emission Dispatch Problem

  • Author

    Jeyakumar, D.N. ; Venkatesh, P. ; Lee, Kwang Y.

  • Author_Institution
    P.S.N.A Coll. of Eng., Dindigul
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    1162
  • Lastpage
    1167
  • Abstract
    This paper describes a new multi-objective evolutionary programming (MOEP) method to solve the combined economic emission dispatch (CEED) problem. CEED is a multi-objective optimization problem by considering the fuel cost and emission as the objectives. It is converted into single objective optimization problem using weighted sum method. Hence the MOEP is proposed by employing the non-dominated solution ranking as selection mechanism for the bi-objective CEED problem. The developed algorithm is tested for a three-unit and a six-unit system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective CEED problem in a single run.
  • Keywords
    Pareto optimisation; emission; evolutionary computation; load dispatching; power system economics; distributed Pareto optimal solutions; economic emission dispatch problem; fuel cost; multiobjective evolutionary programming; selection mechanism; six-unit system; three-unit system; weighted sum method; Atmosphere; Cost function; Environmental economics; Fuel economy; Genetic algorithms; Genetic programming; Power generation; Power generation economics; Power system economics; Testing; Combined economic emission dispatch; Pareto optimal solutions; evolutionary programming; non-dominated solution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4371122
  • Filename
    4371122