Review on Implementation of Various Soft computing Techniques for Tuning Conventional PI Controllers in an HVDC Transmission System

Authors

  • Dr. S. Seenivasan  Assistant Professor, Department of Electrical Engineering, Annamalai University, Annamalainagar, Tamil Nadu, India
  • S. Vadivel  Assistant Professor, Department of Electrical Engineering, Annamalai University, Annamalainagar, Tamil Nadu, India

Keywords:

HVDC transmission system, Converter control, PI controllers, Tuning, Fault Recovery and Soft computing techniques

Abstract

The converter control has a major role to play in avoiding large variations of the DC link current and voltage to attain a reasonable performance of the HVDC system. Conventionally, the controllers used for rectifier and inverter pole current control and inverter extinction angle control are PI controller with fixed gains and can operate well over a narrow range. Many researchers have reported, the HVDC system based on the fixed gain PI controllers cause instability under various abnormal conditions. The problems due to conventional PI controllers for converter controls are inadequate to tune its gain for different operating conditions. To overcome this drawback intelligent technique have been introduced such as fuzzy, neural network, adaptive neuro fuzzy, improved particle swarm optimization, etc., for proper tuning of the controller parameters. In this paper, the literature on the implementation of various soft computing techniques for tuning conventional PI controllers in an HVDC transmission system are presented.

References

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International Journal of Scientific Research in Science and Technology

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Published

2017-03-30

Issue

Volume 3, Issue 3, March-April-2017

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Research Articles

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How to Cite

[1]
Dr. S. Seenivasan, S. Vadivel, " Review on Implementation of Various Soft computing Techniques for Tuning Conventional PI Controllers in an HVDC Transmission System, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 3, pp.778-782, March-April-2017.