Application of Hopfield neural network for distribution network’s reconfiguration

Nguyen Tung Linh; Pham Thuong Cat

doi:10.15625/1813-9663/30/2/3614

Application of Hopfield neural network for distribution network’s reconfiguration

Authors

Nguyen Tung Linh Trường Đại học Điện lực
Pham Thuong Cat

DOI:

https://doi.org/10.15625/1813-9663/30/2/3614

Keywords:

Distribution network, Hopfield neural network, reconfiguration, power losse

Abstract

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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Author Biography

Nguyen Tung Linh, Trường Đại học Điện lực

Nguyen Tung Linh was born 1982. He is working now in postgraduate department at Electric power university. His current research interests include: Power system, application information for power system, intelligent power system, automatic grid distribution, reconfiguration distribution network

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Published

10-06-2014

How to Cite

[1]

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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Issue

Vol. 30 No. 2 (2014)

Section

Cybernetics

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