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Research Article | Open Access |

Network Reconfiguration for Minimizing Power Loss by Moth Swarm Algorithm

Author 1: Thuan Thanh Nguyen Author 2: Duong Thanh Long
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 11, No. 7 · Published 2020 · Cited by 8

DOI: https://doi.org/10.14569/IJACSA.2020.0110705

Abstract

This paper presents a network reconfiguration approach for minimizing power loss of the distribution system based on moth swarm algorithm (MSA). The MSA is a recent metaheuristic inspired from the navigational technique of moths in the dark for finding food sources. For searching optimal solution, MSA used three different mechanisms of generating new solutions consisting of Lévy-flights, Gaussian walks and spiral flight. The effectiveness of MSA is validated on two distribution systems consisting of the 33-nodes and 69-nodes. The simulation results are compared to particle swarm optimization and other available approaches in the literature. The calculated results on the test systems show that MSA can be an effective and reliable tool for the NR problems.

Keywords

How to Cite this Article

Nguyen, T. T., & Long, D. T. (2020). Network Reconfiguration for Minimizing Power Loss by Moth Swarm Algorithm. International Journal of Advanced Computer Science and Applications, 11(7). https://doi.org/10.14569/IJACSA.2020.0110705

Nguyen, Thuan Thanh, and Duong Thanh Long. "Network Reconfiguration for Minimizing Power Loss by Moth Swarm Algorithm." International Journal of Advanced Computer Science and Applications, vol. 11, no. 7, 2020, https://doi.org/10.14569/IJACSA.2020.0110705.

@article{Nguyen2020,
  title     = {Network Reconfiguration for Minimizing Power Loss by Moth Swarm Algorithm},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {7},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Thuan Thanh Nguyen and Duong Thanh Long},
  doi       = {10.14569/IJACSA.2020.0110705},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110705}
}

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