• DocumentCode
    157613
  • Title

    Solar units planning using continuous genetic algorithm to reduce energy loss cost of the distribution system

  • Author

    Sadeghi, Mohammadreza ; Kalantar, Mohsen

  • Author_Institution
    Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
  • fYear
    2014
  • fDate
    10-12 May 2014
  • Firstpage
    127
  • Lastpage
    131
  • Abstract
    This paper focuses on solar units planning problem using continuous genetic algorithm to reduce energy loss cost of the distribution system from probabilistic point of view. As the solar radiance have an intermittent nature, so all of the studies related to these technologies have a probabilistic nature. In this paper, all of the possible states of solar unit generations are considered with their probabilities. So, the probabilistic energy loss cost of the distribution system is achieved. The purpose of this paper is to find the best place and size of the solar units to reduce the probabilistic power loss of the distribution system. The proposed method is applied on a 9 bus test distribution system using GAMS software. The results show a significant reduction in energy loss cost of the distribution system in each state of solar unit generations.
  • Keywords
    genetic algorithms; photovoltaic power systems; power distribution planning; probability; 9 bus test distribution system; GAMS software; continuous genetic algorithm; energy loss cost reduction; probabilistic energy loss cost; probabilistic nature; solar radiance; solar unit generations; solar units planning problem; Energy loss; Genetic algorithms; Planning; Power generation; Power systems; Probabilistic logic; Software; PV Module; Probabilistic Calculation; Rayleigh Probability Distribution Function; Solar Unit Planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2014 14th International Conference on
  • Conference_Location
    Krakow
  • Print_ISBN
    978-1-4799-4661-7
  • Type

    conf

  • DOI
    10.1109/EEEIC.2014.6835850
  • Filename
    6835850