Power enhancement in a grid connected solar PV System by using PLL-neural based converter

Authors

  • Avinash kumar M. Tech. Scholar, Dept. of Electrical & Electronics Engineering, Corporate Institute of Science & Technology, Bhopal
  • Vivek Kumar Kostha Assistant professor, Dept. of Electrical & Electronics Engineering, Corporate Institute of Science & Technology, Bhopal
  • Satyam Kumar Prasun M. Tech. Scholar, Dept. of Electrical & Electronics Engineering, Corporate Institute of Science & Technology, Bhopal

DOI:

https://doi.org/10.24113/ijoscience.v5i11.235

Abstract

This work deals with neural network control algorithm-based grid connected to solar photo voltaic (PV) system consisting of DC-AC converter. The reference solar-grid current for three-leg VSC are estimated using neural network control algorithm. The neural network control algorithm based solar PV system is modeled in MATLAB R2018a along with SIMULINK.. This study presents an artificial neural network-based controller for regulating the level of active and reactive power output. First, the three phase currents from the VSI are measured and compared with the three reference currents. The neural network is trained to have minimum output error. It was concluded that the power output from the system was   found to be190 KVA in case of system having no intelligent controller and 700 KVA in case of system with AAN based control. The voltage of output is maintained to be 20 kV in the grid system for analysis purpose. Thus the proposed control is expected to be implemented in the renewable energy resources for better output.

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References

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Published

11/19/2019

How to Cite

kumar, A., Kostha, V. K., & Prasun, S. K. (2019). Power enhancement in a grid connected solar PV System by using PLL-neural based converter. SMART MOVES JOURNAL IJOSCIENCE, 5(11), 5–13. https://doi.org/10.24113/ijoscience.v5i11.235