Enhanced Damping of Power Oscillations Using a Advance Optimized-Tuned Deep Neural Framework for Power System Stabilizer Design
Pratik R. Dhulap
, Prof. Ganesh G. Mhatre
Power system stabilizer, Power oscillation, Deep neural network, Convolutional neural network, Grey wolf optimization, power oscillation, single machine infinite bus test system
Large-scale interconnections and a variety of structural configurations have made modern power networks more complex, making them more vulnerable to disruptions like low-frequency electromechanical oscillations, transmission faults, and generator outages. Effective damping techniques are essential because low-frequency oscillations are one of the main threats to safe and dependable system operation. In this work, a Convolutional Neural Network (CNN) with hyperparameters optimized using the Grey Wolf Optimizer (GWO) is integrated into an advanced Power System Stabilizer (PSS) design. To guarantee adaptive and reliable stabilizer performance, GWO is used to systematically tune the CNN structure, including convolutional layers and filter dimensions. Extensive simulations under a range of operating conditions are used to test the proposed GWO-CNN-based PSS on a Single-Machine Infinite Bus (SMIB) system. The suggested method’s improved damping capability is highlighted by a comparison with traditional PSS designs, proving its efficacy in reducing oscillations and enhancing system stability in general
"Enhanced Damping of Power Oscillations Using a Advance Optimized-Tuned Deep Neural Framework for Power System Stabilizer Design", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 9, page no.a600-a606, September-2025, Available :https://ijsdr.org/papers/IJSDR2509072.pdf
Volume 10
Issue 9,
September-2025
Pages : a600-a606
Paper Reg. ID: IJSDR_304909
Published Paper Id: IJSDR2509072
Downloads: 00082
Research Area: Science and Technology
Country: Raigad, Mumbai, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
