• DocumentCode
    3317944
  • Title

    A new algorithm based on non-dominated sorting differential evolution for multi-objective optimal load dispatch

  • Author

    Peng, Chunhua ; Sun, Huijuan ; Guo, Jianfeng ; Li, Haishan

  • Author_Institution
    Dept. of Electr. & Electron. Eng., East China Jiaotong Univ., Nanchang, China
  • fYear
    2009
  • fDate
    8-11 Aug. 2009
  • Firstpage
    565
  • Lastpage
    569
  • Abstract
    A multi-objective optimal load dispatch model is proposed for minimizing both total purchase cost and emissions considering the difference of power purchase price and emissions between each power plant. And a new NSDE algorithm, which is organic integration of Pareto non-dominant sorting and differential evolution algorithm and improves the crowding distance mechanism and mutation strategic in evolution effectively, is designed for the model. Simulation on a power system with 6 generating unit shows that the algorithm can overcome disadvantages in conventional multi-objective algorithms with apparent improvement on search speed, integrality of Pareto front, distribution of non-dominant solutions and convergence and can achieve more accurate and diversiform Pareto non-dominant optimal set.
  • Keywords
    Pareto analysis; power generation dispatch; power generation economics; crowding distance mechanism; diversiform Pareto nondominant optimal set; multiobjective optimal load dispatch; mutation strategic; nondominated sorting differential evolution; power plant; power purchase price; total purchase cost; Air pollution; Atmospheric modeling; Cities and towns; Cost function; Genetic algorithms; Genetic mutations; Power generation; Power system modeling; Power system simulation; Sorting; Differential Evolution; Load dispatch; Multi-objective optimization; Nondominated sorting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4519-6
  • Electronic_ISBN
    978-1-4244-4520-2
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2009.5234886
  • Filename
    5234886