• DocumentCode
    622140
  • Title

    A new swarm intelligence technique for solving economic dispatch problem

  • Author

    Sulaiman, Mohd H. ; Zakaria, Zetty N. ; Rashid, M. I. Mohd ; Rahim, Siti Rafidah Abdul

  • Author_Institution
    Fac. of Electr. & Electron. Eng., Univ. Malaysia Pahang, Pekan, Malaysia
  • fYear
    2013
  • fDate
    3-4 June 2013
  • Firstpage
    199
  • Lastpage
    202
  • Abstract
    This paper presents a new swarm intelligence (SI) technique to solve economic dispatch (ED) problems in power system. As been acknowledge that ED is one of the most complex optimization problem to be performed in the planning and operation of a power system which is to determine the optimal generation scheduling so that the minimum cost can be obtained. In addition, the effect of equality and inequality constraints that embedded in this problem makes ED harder to solve by using conventional techniques. In this paper, a recent SI technique, namely differential search (DS) algorithm is implemented to solve ED problem. DS simulates the Brownian-like random-walk movement used by organisms to migrate. In order to demonstrate the effectiveness of DS, two test systems viz. 15-units system and TAIPOWER 40-units system are utilized as test cases and compared to the other technique. instructions give you basic guidelines for preparing papers for conference proceedings.
  • Keywords
    power generation dispatch; power generation planning; swarm intelligence; 15-units system; Brownian-like random-walk movement; DS algorithm; ED; SI technique; TAIPOWER 40-units system; differential search algorithm; economic dispatch problem; optimal generation scheduling; power system operation; power system planning; swarm intelligence technique; Conferences; Economics; Generators; Optimization; Particle swarm optimization; Power engineering; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Optimization Conference (PEOCO), 2013 IEEE 7th International
  • Conference_Location
    Langkawi
  • Print_ISBN
    978-1-4673-5072-3
  • Type

    conf

  • DOI
    10.1109/PEOCO.2013.6564542
  • Filename
    6564542