Application of Hopfield neural network for distribution network’s reconfiguration

Nguyen Tung Linh, Pham Thuong Cat
Author affiliations


  • Nguyen Tung Linh Trường Đại học Điện lực
  • Pham Thuong Cat



Distribution network, Hopfield neural network, reconfiguration, power losse


In power systems, power losses of system distribution networks take large proportion. In order to reduce power waste we have applied a variety of methods such as: improving the grid, setting the capacitor capacity and suitable location, optimizing operating system, etc. This paper refers to a reconfiguration method for reducing such losses. Reconfiguration method is a method of finding an optimal network reconfiguration to operate the electricity network to the smallest losses. The restructuring of the classical method would require a lot of time for the distribution networks having many nodes, and unsuitably for the fast response. This paper presents the use of Hopfield neural network to find an optimal reconfiguration of the distribution network. The proposed method is tested on the data grid form of the IEEE.

The result of the proposed method is compared with the similar results by the other method and shows that optimal function has a minimum.


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How to Cite

N. T. Linh and P. T. Cat, “Application of Hopfield neural network for distribution network’s reconfiguration”, JCC, vol. 30, no. 2, pp. 81–92, Jun. 2014.




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