ISSN2456-3315
Impact Factor10.57
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ESTD2016
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Paper Title
Using Artificial Neural Network power quality enhancement based DVR
Authors
Ashabai Shivaji Gadhave , Malad H.M. , Patil V.J , Salunkhe S.H. , More Divyani S.
Keywords
power quality, DVR, enhancement, voltage sags, dynamic, stability, voltage swell
Abstract
Power quality is crucial in modern power systems. Including the stability and reliability of electrical supply, voltage levels, frequency, and the presence of disturbances like harmonics, surges, or sags. Voltage harmonics sags, and swells can indeed damage sensitive equipment. As the reliance on sensitive and sophisticated equipment grows, maintaining high power quality becomes even more critical. The use of an artificial neural network (ANN) controller voltage sag and swell is compensated by DVR . For voltage source converter (VSC) switching the generation of reference voltage for, the voltage conversion from rotating vectors to stationary frame, synchronous reference frame (SRF) theory is applied. Using MATLAB software The DVR Control Strategy and its performance is simulated. The ANN controller, by being able to approximate complex functions and adjust its behavior based on real-time input. The Dynamic Voltage Restorer (DVR) is indeed a specialized device designed to protect sensitive loads from voltage disturbances in power distribution systems. The efficiency of the control technique used for managing inverter switching is a critical factor in the overall performance of a Dynamic Voltage Restorer (DVR). The power quality of non- linear systems such as a Dynamic Voltage Restorer (DVR). Comparison of the ANN controller with the conventional Proportional Integral controller (PI), which showed ANN controller's superior performance with less Total Harmonic Distortion (THD) it is also shown a detailed.
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IJRTI — journal style
"Using Artificial Neural Network power quality enhancement based DVR", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 3, page no.a344-a347, March-2025, Available :https://ijrti.org/papers/IJRTI2503042.pdf
APA — 7th edition
Gadhave, A. S., H.M., M., V.J, P., S.H., S., & S., M. D. (2025). Using Artificial Neural Network power quality enhancement based DVR. International Journal for Research Trends and Innovation, 10(3), a344-a347. https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042
MLA — 9th edition
Gadhave, Ashabai Shivaji, et al. "Using Artificial Neural Network power quality enhancement based DVR." International Journal for Research Trends and Innovation, vol. 10, no. 3, 2025, pp. a344-a347, https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042.
Chicago — 17th, bibliography
Gadhave, Ashabai Shivaji, et al. "Using Artificial Neural Network power quality enhancement based DVR." International Journal for Research Trends and Innovation 10, no. 3 (2025): a344-a347. https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042.
Harvard — author–date
Gadhave, A.S. et al. (2025) 'Using Artificial Neural Network power quality enhancement based DVR', International Journal for Research Trends and Innovation, 10(3), pp. a344-a347. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042
IEEE — numbered reference
A. S. Gadhave, M. H.M., P. V.J, S. S.H. and M. D. S., "Using Artificial Neural Network power quality enhancement based DVR," IJRTI, vol. 10, no. 3, pp. a344-a347, Mar. 2025.
Vancouver — biomedical
Gadhave AS, H.M. M, V.J P, S.H. S, S. MD. Using Artificial Neural Network power quality enhancement based DVR. IJRTI. 2025 Mar;10(3):a344-a347.
AMA — 11th edition
Gadhave AS, H.M. M, V.J P, S.H. S, S. MD. Using Artificial Neural Network power quality enhancement based DVR. IJRTI. 2025;10(3):a344-a347. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2503042,
author = {Ashabai Shivaji Gadhave and Malad H.M. and Patil V.J and Salunkhe S.H. and More Divyani S.},
title = {Using Artificial Neural Network power quality enhancement based DVR},
journal = {International Journal for Research Trends and Innovation},
volume = {10},
number = {3},
pages = {a344-a347},
year = {2025},
month = {March},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Gadhave, Ashabai Shivaji
AU - H.M., Malad
AU - V.J, Patil
AU - S.H., Salunkhe
AU - S., More Divyani
TI - Using Artificial Neural Network power quality enhancement based DVR
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 10
IS - 3
PY - 2025
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042
SP - a344-a347
ER -
Issue
Volume 10 Issue 3,
March-2025
Pages : a344-a347
Other Publication Details
Paper Reg. ID
IJRTI_201190
Published Paper ID
IJRTI2503042
Downloads
205,619
Research Area
Engineering
Country
SOLAPUR, MAHARASHTRA, India
Published
March 2025
Published Paper PDF
https://ijrti.org/papers/IJRTI2503042.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2503042
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
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Open
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
