Development of a genetic algorithm for placing power supply sources in a distributed electric network

Abstract

<p>The problem of substantiation of developing complex distribution systems of electric power supply was considered as a hierarchy of problems at the first stage of which the problem of choosing a rational configuration of the power system was solved. A mathematical model of solution of the problem of optimal placement of several power sources in the power supply system and assigning to them consumers using genetic programming algorithms was developed. The proposed methods make it possible to obtain optimal routes of transmission lines connecting consumers with power sources taking into account the terrain restrictions.</p><p>A modification of a simple genetic algorithm based on which an information system was implemented was developed. This system solves the problem of combinatorial optimization with respect to the choice of optimal location of power sources in a distributed electrical network.</p>Calculation time was estimated depending on the problem parameters. It was shown that the developed algorithm provides minimum computation time for problems of small and medium dimensionality. The results of solution of the problem for a concrete example demonstrate advantage of the genetic approach over the method of full enumeration. The results obtained can be successfully applied to solve the problem of optimizing placement of power sources in a distributed electrical network

Authors and Affiliations

Ievgen Fedorchenko, Andrii Oliinyk, Alexander Stepanenko, Tetiana Zaiko, Serhii Korniienko, Nikita Burtsev

Keywords

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  • EP ID EP667117
  • DOI 10.15587/1729-4061.2019.180897
  • Views 83
  • Downloads 0

How To Cite

Ievgen Fedorchenko, Andrii Oliinyk, Alexander Stepanenko, Tetiana Zaiko, Serhii Korniienko, Nikita Burtsev (2019). Development of a genetic algorithm for placing power supply sources in a distributed electric network. Восточно-Европейский журнал передовых технологий, 5(3), 6-16. https://europub.co.uk/articles/-A-667117