• DocumentCode
    622245
  • Title

    Loss minimization of distribution system with photovoltaic injection using Swarm evolutionary programming

  • Author

    Ahmad, N.A. ; Musirin, I. ; Sulaiman, Shahril Irwan

  • Author_Institution
    Centre for Electr. Power Eng., Univ. Teknol. Mara, Shah Alam, Malaysia
  • fYear
    2013
  • fDate
    3-4 June 2013
  • Firstpage
    752
  • Lastpage
    757
  • Abstract
    This paper presents the study of an optimization technique that is developed to locate the optimal location and the size (power rating) of Distributed Generation (DG) for its installation to a distribution system. The type of the chosen DG is photovoltaic (PV). In this study, the author proposes the new technique called Swarm Evolutionary (SEP) technique where the concept of applying and substituting the concept of Particle Swarm Optimization (PSO) in some part of Evolutionary Programming (EP) is applied on IEEE 69 radial bus distribution system. The result is then compared with the result from classic EP and Artificial Immune System (AIS). The objective is to minimize overall system power loss and improving voltage profile. The proposed optimization technique is developed under MATLAB programming. Test results indicate that Swarm EP technique can reduce the total system loss and improve the voltage profile better than EP and AIS for the distribution system under various loading conditions.
  • Keywords
    artificial immune systems; distributed power generation; evolutionary computation; particle swarm optimisation; photovoltaic power systems; AIS; IEEE 69 radial bus distribution system; Matlab programming; SEP; artificial immune system; distributed generation; loading condition; loss minimization; particle swarm optimization; photovoltaic injection; swarm evolutionary programming; voltage profile; Convergence; Equations; Optimization; Power engineering; Programming; Sociology; Statistics;
  • 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.2013.6564647
  • Filename
    6564647