Application of Neural Network Based Data Security in to LFC of a Two Area Power System

Authors

  • T. Rathimala Assistant Professor, Department of Computer and Information Science, Annamalai University, Annamalai Nagar, Tamil Nadu, India
  • R. Francis Assistant Professor, Government Engineering College, Bargur, Tamil Nadu, India
  • M. Kamarasan Assistant Professor, Department of Computer and Information Science, Annamalai University, Annamalai Nagar, Tamil Nadu, India

DOI:

https://doi.org/10.51983/ajes-2018.7.2.2281

Keywords:

Back Propagation Neural Networks, Data Security, Cryptography, Load-Frequency Control, Integral Controller

Abstract

The paper is concentrated with the study of design of a data security system based on neural networks. This data security method added Load-Frequency Control of reheat interconnected two area power systems problems with non-linearity. The neural network control is incorporated to load-frequency control in power systems. Elman Recurrent neural network is involves forecasting controller and system’s output. The system was simulated and the frequency variations in area 1 and area 2 and tie-line power variations for 1% step-load disturbance in area 1 were obtained. The comparison due to frequency variations and tie-line power deviations for the two area interconnected thermal power system. The result data of different keys were taken as test data, encrypted, decrypted and compared with the original data. The results have ensured better its advantages over conventional techniques.

References

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Published

09-08-2018

How to Cite

Rathimala, T., R. Francis, & M. Kamarasan. (2018). Application of Neural Network Based Data Security in to LFC of a Two Area Power System. Asian Journal of Electrical Sciences, 7(2), 19–23. https://doi.org/10.51983/ajes-2018.7.2.2281

Issue

Vol. 7 No. 2 (2018): July-December 2018

Section

Articles

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Copyright (c) 2018 The Research Publication

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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