Optimization based variable learning factor least mean square algorithm to control DVR in infected grid systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a variable learning rate least mean square control algorithm has been proposed to control Dynamic Voltage Restorer for compensating the disturbances present in the supply source side of a distribution network. The proposed control algorithm is equipped with an optimization algorithm based on Slime Mould for the tuning of PI controller gains. The topology of the Dynamic Voltage Restorer presented in this paper is a voltage source converter with capacitor as an energy storage device that is utilized for the compensation of four various disturbances in the supply voltage viz. voltage sag, voltage swell, unbalance, and voltage distortions. System performance has been validated via simulation using MATLAB/Simulink.

Original languageBritish English
Title of host publication9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728156729
DOIs
StatePublished - 16 Dec 2020
Event9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020 - Jaipur, India
Duration: 16 Dec 202019 Dec 2020

Publication series

Name9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020

Conference

Conference9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020
Country/TerritoryIndia
CityJaipur
Period16/12/2019/12/20

Keywords

  • Distortions
  • Learning Rate
  • Least Mean Square
  • Optimization
  • Power Quality
  • Sag
  • SMA

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