APPLICATION OF NEURAL NETWORKS FOR VOLTAGE DIPS DETECTION ON THE EXAMPLE OF TEST GRIDS OPERATION

Authors

  • Ivan Vasić Autor
  • Vladimir Katić Autor
  • Aleksandar Stanisavljević Autor

DOI:

https://doi.org/10.24867/12BE08Vasic

Keywords:

IEEE 13-bus test grid, neural networks, voltage dips

Abstract

In the thesis applications of neural networks in power engineering is described, especially in MATLAB software package. A case study of fault detection in the IEEE13 test grid with inserted renewable energy resource is given. It is shown that neural network gives great result in this branch, following impressive results for fault detection in IEEE13 test grid.

References

[1] D. J. Đozić: „Upotreba veštačkih neuronskih mreža za predviđanje ponašanja i upravljanje složenim elektroenergetskim sistemima“, Fakultet tehničkih nauka, Doktorska disertacija, Novi Sad, 2020.
[2] V. A. Katić, A.M. Stanisavljević, “Smart Detection of Voltage Dips Using Voltage Harmonics Footprint”, IEEE Transaction on Industry Application, Vol.54, No.5, Sep./Oct. 2018, pp.5331-5342,
[3] M. T. Hagh: “Application of Neural Networks in Power Systems”, WAS, Engineering and Technology, No.6 2005, pp.53-57.
[4] L. H. Hassan, M. Moghavvemi, Haider A.F. Almurib, Otto Steinmayer: “Current state of neural networks applications in power system monitoring and control“
[5] K.-L. Du, M.N.S. Swamy: “Neural Networks and Statistical Learning”, Springer-Verlag London, 2014.
[6] M. M. Milosavljević: „Veštačka inteligencija“, Univerzitet Singidunum, Beograd, 2015.

Published

2021-03-05

Issue

Section

Electrotechnical and Computer Engineering