Fault Response Improvement in Power system using ANN controlled DVR

This research article proposes an advanced fault response improvement technique for power systems using an Artificial Neural Network (ANN)-controlled Dynamic Voltage Restorer (DVR). The DVR, a versatile FACTS device, is capable of mitigating voltage sags and swells, improving power quality, and enhancing system stability. By integrating an ANN into the DVR control system, the proposed approach aims to significantly enhance the device's response time and accuracy in addressing power quality disturbances. The ANN is trained on a comprehensive dataset of fault scenarios, enabling it to learn optimal control strategies. The effectiveness of the proposed ANN-controlled DVR is evaluated through extensive simulations under various fault conditions. The results demonstrate substantial improvements in voltage recovery time, overshoot, and undershoot, leading to enhanced system reliability and performance.