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@article{165771,
        author = {Manne Praful yadav and P Sujatha},
        title = {Fault ride through capability enhancement of grid connected system using ANN based DVR},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {11},
        number = {1},
        pages = {1621-1627},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165771},
        abstract = {In order to analyze electrical interference, such as voltage dips, swells, and harmonics, this article explains the best practices of restoring electrical power during the interference. Prediction of faults and early restorer is typically the base to maintain system balanced. The rated load voltage and segmentation angle are controlled by the controller, which is purely based on dq0 conversion technology and ANN. We have performed the simulation study of a three-phase rectifier with a non-linear balanced resistor-capacitor DC load. Furthermore, using a programmable AC power supply, voltage dips and spikes on the subsequent power side were investigated. The DVR effectively reduces interference with the least amount of interference according to simulation results. The MATLAB/Simulink environment was used to analyze the DVR's overall performance. We also learned about the various devices used for this purpose and further explored the design features of a dynamic voltage restorer. It is about the principle of operation and various operating modes, which improve the quality of energy in the network of distribution and power supply. MATLAB/Simulation is used in all of this work to demonstrate how a DVR operates in real time},
        keywords = {Power Quality issues, THD-Total Harmonic Distortion, ANN- Artificial Neural Network, DVR-Dynamic Voltage Restorer, },
        month = {},
        }