Adaptive Control Of Grid Integrated Photovoltaic Using Recurrent Neural Network

Authors

  • R. Senthil Kumar Research scholar, Department of EEE SCSVMV University, Tamil Nadu, India
  • Prabakaran S. Associate Professor, Department of EEE SCSVMV University, Tamil Nadu, India
  • S. Sentamil Selvan HOD, Department of EEE SCSVMV University, Tamil Nadu, India

Keywords:

Power Quality, Total Harmonic Distortion (THD), Distribution Grid Synchronization, PV integration, RNN

Abstract

The Photovoltaic (PV) demand is increasing day by day globally. To meet the demand PV is generally connected to the distribution grid. To achieve higher efficiency of the PV integrated distribution grid, this paper proposes an algorithm named Recurrent Neural Network (RNN) for the control of the PV integrated distribution grid system. This algorithm controls the Voltage source converter (VSC) by aiming for harmonic mitigation, load balancing and other power quality problems. This algorithm focuses to deliver maximum power on the grid side VSC. The proposed technique is designed and simulated in a MATLAB environment using SIMULINK. The results confirm that the Total Harmonic Distortion is reduced as recommended by the IEEE-519 standard.

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Schematic structure of RNN

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Published

17.05.2023

How to Cite

Kumar, R. S. ., S., P. ., & Selvan, S. S. . (2023). Adaptive Control Of Grid Integrated Photovoltaic Using Recurrent Neural Network. International Journal of Intelligent Systems and Applications in Engineering, 11(6s), 295–300. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2856

Issue

Vol. 11 No. 6s (2023)

Section

Research Article

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