@inproceedings{cb4ae9a386e6445989c9cf0aa1b683c0,
title = "Optimization based variable learning factor least mean square algorithm to control DVR in infected grid systems",
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.",
keywords = "Distortions, Learning Rate, Least Mean Square, Optimization, Power Quality, Sag, SMA",
author = "Naidu, \{Talada Appala\} and Ahmed Al-Durra and El-Fouly, \{Tarek H.M.\} and Hatem Zeineldin",
note = "Funding Information: APPENDIX System Parameters for Simulation Non-ideal AC mains: 410 V, 50Hz; sensitive inductive load: 12 kVA, 0.8 p.f. (lag.), Injection transformers: 3 kVA each, 100/100V; Ripple filter: Rf=2Ω, Cf=30µF; interfacing inductor Li=1 mH; DC-bus voltage: 300V; DC-bus capacitor, CDC=1200 µF; Switching frequency used with unipolar scheme (fs)=2.5kHz, Cutoff frequency of low-pass filter at DC bus= 8Hz, Cutoff frequency of low-pass filter at AC bus= 10Hz; sampling time (Ts)=20 µsec; ACKNOWLEDGMENT This work was supported by the Khalifa University of Science and Technology under Award No. CIRA-2019-049. Publisher Copyright: {\textcopyright} 2020 IEEE.; 9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020 ; Conference date: 16-12-2020 Through 19-12-2020",
year = "2020",
month = dec,
day = "16",
doi = "10.1109/PEDES49360.2020.9379450",
language = "British English",
series = "9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020",
address = "United States",
}