Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/9854,
  title    = {Optimal Embedded Generation Allocation in Distribution System Employing Real Coded Genetic Algorithm Method},
  author    = {Mohd Herwan Sulaiman and  Omar Aliman and  Siti Rafidah Abdul Rahim},
  country   = {},
  institution={},
  abstract  = {This paper proposes a new methodology for the
optimal allocation and sizing of Embedded Generation (EG)
employing Real Coded Genetic Algorithm (RCGA) to minimize the
total power losses and to improve voltage profiles in the radial
distribution networks. RCGA is a method that uses continuous
floating numbers as representation which is different from
conventional binary numbers. The RCGA is used as solution tool,
which can determine the optimal location and size of EG in radial
system simultaneously. This method is developed in MATLAB. The
effect of EG units- installation and their sizing to the distribution
networks are demonstrated using 24 bus system.},
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {4},
  number    = {2},
  year      = {2010},
  pages     = {312 - 317},
  ee        = {http://waset.org/publications/9854},
  url       = {http://waset.org/Publications?p=38},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 38, 2010},
}