Enhanced Grid Stability with ANN-Tuned Four-Leg Dynamic Voltage Restorer in Grid-Connected Systems
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Abstract
Unbalanced loads are a typical source of power quality problems in contemporary grid-connected systems, including voltage sags and swells. Electrical system stability and performance can be severely compromised by these disruptions. This study aims to solve this problem by simulating a Dynamic Voltage Restorer (DVR) and an ANN-tuned Four-Leg Voltage Source Converter (VSC). By adding a neutral leg to the four-legged design, the DVR is better equipped to deal with imbalanced situations and direct current in a straight line. The key objective of this research is to enhance grid stability and improve power quality by mitigating voltage disturbances. The ANN-based control strategy dynamically adjusts the DVR’s output, ensuring optimal compensation for voltage sags, swells, and harmonic distortion. Using Matlab/Simulink simulations, the proposed system's performance is compared to traditional control methods such as Sliding Mode Controllers (SMC), demonstrating superior results. Simulation results show that the ANN-tuned DVR significantly reduces Total Harmonic Distortion (THD) under various operating conditions, keeping THD well below the IEEE standard of 5%. The ANN-based control system outperforms conventional methods by improving load voltage stabilization and reducing voltage distortions. These findings suggest that the ANN-tuned four-leg DVR is a promising solution for enhancing power quality in grid-connected systems, with potential applications in future smart grids and renewable energy integration.
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