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DOI: 10.14569/IJARAI.2016.050202
PDF

Optimal Network Reconfiguration with Distributed Generation Using NSGA II Algorithm

Author 1: Jasna Hivziefendic
Author 2: Amir Hadžimehmedovic
Author 3: Majda Tešanovic

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 5 Issue 2, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: This paper presents a method to solve electrical network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and energy not supplied function in distribution system. A method based on NSGA II multi-objective algorithm is used to simultaneously minimize two objective functions and to identify the optimal distribution network topology. The constraints of voltage and branch current carrying capacity are included in the evaluation of the objective function. The method has been tested on radial electrical distribution network with 213 nodes, 248 lines and 72 switches. Numerical results are presented to demonstrate the performance and effectiveness of the proposed methodology.

Keywords: radial distribution network; distributed generation; genetic algorithms; NSGA II; loss reduction

Jasna Hivziefendic, Amir Hadžimehmedovic and Majda Tešanovic, “Optimal Network Reconfiguration with Distributed Generation Using NSGA II Algorithm” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 5(2), 2016. http://dx.doi.org/10.14569/IJARAI.2016.050202

@article{Hivziefendic2016,
title = {Optimal Network Reconfiguration with Distributed Generation Using NSGA II Algorithm},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2016.050202},
url = {http://dx.doi.org/10.14569/IJARAI.2016.050202},
year = {2016},
publisher = {The Science and Information Organization},
volume = {5},
number = {2},
author = {Jasna Hivziefendic and Amir Hadžimehmedovic and Majda Tešanovic}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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