• Augustine kujur
• Aman Banjare
• Megha Dewangan
• Ankush Paikra
• Jagannath Patra

In the modern day, maintaining the quality of supply has made the issue of power quality extremely important. The present generation's quality of life is greatly enhanced by electrical energy. Modern gadgets like computers and electric motors require electricity to function. One major issue facing today's power system is power quality, which can have an impact on consumers as well as utilities. For the equipment to work more effectively, high-quality supplies are required. In transmission networks, one of the most prevalent problems with power quality is voltage sag/swell. Many modern specialized devices are available to reduce such problems. Of them, the Dynamic Voltage Restorer (DVR) is the most cost-effective and effective. To handle problems with erratic voltage, current, or frequency in the distribution grid, the Distribution Flexible AC Transmission System (D-FACTS) can be fitted with a DVR. The controller that provides signals to the system uses an artificial neural network. The sag issue is mitigated by DVR that is based on artificial neural networks. The large number of nonlinear loads in modern power systems has a significant impact on the power supply's quality. Power quality problems including harmonics and voltage sag and rise frequently occur. Here, a novel infinite level inverter (ILI) topology is presented in order to provide a dynamic voltage restorer (DVR) that can alleviate voltage swell and sag issues. When compared to a three-phase ILI, DVRs using traditional modulation techniques like sine PWM and space vector PWM based bridge inverters require higher DC link voltages.

Dynamic Voltage Restorer (DVR) , Artificial Neural Network , PI Controller , Voltage Sag, Voltage swell

"POWER QUALITY IMPROVEMENT USING LEVENBERG MARQUARDT ARTIFICIAL NEURAL NETWORK BASED DYNAMIC VOLTAGE RESTORER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.e476-e489, April-2024, Available :http://www.jetir.org/papers/JETIR2404452.pdf

"POWER QUALITY IMPROVEMENT USING LEVENBERG MARQUARDT ARTIFICIAL NEURAL NETWORK BASED DYNAMIC VOLTAGE RESTORER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppe476-e489, April-2024, Available at : http://www.jetir.org/papers/JETIR2404452.pdf