Enhancement of Power Quality Using Artificial Neural Networks to Implement a Dynamic Voltage Restorer

Registration ID: IJNRD_218591

Published ID: IJNRD2404480

DOI: http://doi.one/10.1729/Journal.38970

R. Babu , D. Chandana , T. Harshavardhan , B. Akshay , P. Manikanta

Dynamic Voltage Restorer, PI Controller, Neural Network Controller

Once Dynamic Voltage Restorer knows the precise voltage quality level that the customer needs, they has the ability to offer the least expensive method of reducing voltage dips. The distribution feeder and the DVR are connected in series at medium voltage. One typical method of controlling DVRs is via the PI controller. The traditional controller relies on fixed gains, namely the THD, to lower the THD, which is a restriction of the controller. It is possible to operate a DVR using an ANN. Based on PI and ANN Controller, this work investigates the compensation notion and various DVR control methods. A constant load voltage may be achieved by injecting voltage into the DVR, as shown in comprehensive studies and MATLAB/Simulink simulations.

Published Paper   E-Certificate

R. Babu, D. Chandana, T. Harshavardhan, B. Akshay, & P. Manikanta (April-2024). Enhancement of Power Quality Using Artificial Neural Networks to Implement a Dynamic Voltage Restorer. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), e778-e788. http://doi.one/10.1729/Journal.38970

Volume 9 Issue 4, April-2024

Pages : e778-e788

Paper Reg. ID: IJNRD_218591

Published Paper Id: IJNRD2404480

Downloads: 000121991

Research Area: Electrical Engineering 

Country: KARIMNAGAR, Telangana, India

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Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404480

Crossref DOI: http://doi.one/10.1729/Journal.38970

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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