• DocumentCode
    139014
  • Title

    Implementation of Artificial Bees Colony algorithm on real power line loss allocation

  • Author

    Minhat, A.R. ; Mustafa, M.W. ; Musirin, I. ; Khalid, S. N. Abd

  • Author_Institution
    Fac. of Electr. Eng. (FKE), Univ. Teknol. Malaysia, Skudai, Malaysia
  • fYear
    2014
  • fDate
    24-25 March 2014
  • Firstpage
    658
  • Lastpage
    662
  • Abstract
    Transmission power loss has become a progressing issue these days due to the changes from monopolized to deregulation environment. This can be due to the large transmission power loss which leads to monetary losses. The presence of deregulated power system requires the participants to make decision on transmission line charge. Hence it is necessary to have a method to determine fair, transparent and equitable charges among market participants respectively. This paper proposed a heuristic technique termed as Artificial Bee Colony (ABC) algorithm for real power line allocation for solving the line loss allocation among market participants. In this study ABC Algorithm optimization engine is utilized to solve the real power loss allocation. The proposed technique was validated on IEEE 30 Bus Reliability Test System. Results obtained from the study indicated that the proposed ABC algorithm technique is superior as compared to Particle Swarm Optimization (PSO) technique.
  • Keywords
    electricity supply industry deregulation; optimisation; power transmission reliability; ABC Algorithm optimization engine; IEEE 30 bus reliability test system; artificial bees colony algorithm; deregulated power system; line loss allocation; real power line loss allocation; transmission line charge; transmission power loss; Electrical engineering; Generators; Load flow; Optimization; Propagation losses; Resource management; Sociology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Optimization Conference (PEOCO), 2014 IEEE 8th International
  • Conference_Location
    Langkawi
  • Print_ISBN
    978-1-4799-2421-9
  • Type

    conf

  • DOI
    10.1109/PEOCO.2014.6814509
  • Filename
    6814509