Integration of ANN Controller for AGC in Hydro-Thermal Systems with Dynamic Turbine Time Constants and Variable Power System Loading Conditions
Journal Title: International Journal for Modern Trends in Science and Technology - Year 2024, Vol 10, Issue 11
Abstract
The integration of an Artificial Neural Network (ANN) controller for Automatic Generation Control (AGC) in hydro-thermal power systems presents a novel approach to managing the dynamic and complex nature of modern power grids. This study focuses on enhancing AGC performance by addressing the challenges posed by dynamic turbine time constants and variable power system loading conditions. Traditional AGC methods often fall short in handling these complexities due to their limited adaptability. In contrast, ANN controllers, with their ability to learn and adapt to changing system dynamics, offer a robust solution. The ANN controller is designed to continuously adjust control parameters in real-time, ensuring optimal frequency regulation and stability across varying load conditions. Using MATLAB/SIMULINK, the hydro-thermal system is simulated to evaluate the performance of the ANN controller under different scenarios. The results demonstrate significant improvements in system stability, response time, and frequency regulation compared to conventional control methods. This research highlights the potential of ANN controllers to enhance the reliability and efficiency of AGC in hydro-thermal systems, paving the way for more resilient and adaptive power system management.
Authors and Affiliations
Dr. J. Srinu Naik, P. V. Guru Susmanth, D. Harish Kumar, A. Babu Reddy and A. Jayavardhan
Keywords
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- EP ID EP752213
- DOI https://doi.org/10.46501/IJMTST1011006
- Views 26
- Downloads 0
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