Combined Perturb and Observe and Artificial Neural Network Approach for Maximum Power Point Tracking in Photovoltaic System under Uniformly Shaded Conditions

Authors

  • K. V. Subathra  Assistant Professor, Amrita College of Engineering and Technology, Nagercoil, Kanya Kumari DT (TN), 629901. India

DOI:

https://doi.org/10.32628/IJSRSET2293185

Keywords:

MPPT, Photovoltaic, Artificial Neural Network, Back-propagation

Abstract

Maximum Power Point Tracking (MPPT) of PV system is very much essential for the efficient operation of the solar photovoltaic (PV) system. PV system performance mainly depends on solar insolation and temperature conditions. In this paper combination of Perturb and Observe (P&O) and Artificial Neural Network (ANN) MPPT algorithms is proposed to provide reference voltage to DC-DC boost converter in the PV system under uniform shading conditions. In ANN- based techniques, the maximum power points are acquired by designing ANN models for PV modules. Compared to conventional P&O MPPT method, this approach tracks to the Maximum Power Point (MPP) faster with less fluctuations. The training of the ANN is done with Levenberg Marquardt algorithm and the whole technique is being simulated and studied using MATLAB software.

References

  1. Ratna lka Putri and M.Rifa’I,” Maximum Power Point Tracking Control for Photovoltaic System Using Neural Fuzzy”, International Journal of Computer and Electrical Engineering, Vol.4, No.1, February 2012.
  2. Bader N. Alajmi, Khaled H. Ahmed, Stephen J. Finney, and Barry W. Williams, ‘Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System’, IEEE Transactions on power electronics, VOL.26, NO.4,April 2011.
  3. Hiren Patel and Vivek Agarwal,’ Maximum Power Point Tracking Scheme for PV Systems Operating Under Partially Shaded Conditions’,IEEE Transactions on Industrial electronics, VOL.55,NO.4,April 2008.
  4. S. Premrudeepreechacharn, and N. Patanapirom, “ Solar-Array Modelling and Maximum Power Point Tracking Using Neural Networks”, paper accepted for presentation at 2003 IEEE Bologna power Tech conference, June 23th-26th, Bologna, Italy.
  5. Nicola Femia, Giovanni Petrone, Giovanni Spagnuolo, and Massimo Vitelli,’ Optimization of Perturb and Observe Maximum Power Point Tracking Method’,IEEE Transactions on power electronics VOL.20,NO.4,July 2005.
  6. R.Ramaprabha, B.L.Mathur, “Intelligent Controller based Maximum Power Point Tracking for Solar PV System”, International Journal of Computer Applications (0975 – 8887) Volume 12– No.10, January 2011.
  7. Abdessamia Elgharbi, Dhafer Mezghani, Abdelkader Mami,‘A Maximum power point Tracking method based on Artificial Neural Network for a PV system’, International Journal of Advances in Engineering & Technology, Nov. 2012.
  8. S.Gomathy, S.Saravanan, Dr. S. Thangavel,’Design and Implementation of Maximum Power Point Tracking (MPPT) Algorithm for a Standalone PV System’, International Journal of Scientific & Engineering Research Volume 3, Issue 3, March, 2012.
  9. Hamed Taheri, Zainal Salam, Kashif Ishaque & Syafaruddin ‘A Novel Maximum Power Point Tracking Control of Photovoltaic system Under Partial and Rapidly Fluctuating Shadow Conditions Using Differential Evolution’,IEEE symposium on Industrial Electronics and applications (ISIEA 2010), October 3-5,2010.
  10. Athimulam Kalirasu, Subharensu Sekar Dash.’Simulation of closed Loop Controlled Boost Converter for Solar Installation’Serbian Journal of Electrical Engineering,VOL.7,NO.1,May 2010.
  11. Hong Hee Lee, Le Minh Phuong, Phan Quoc Dzung, Nguyen Truong Dan Vu, Le Dinh Khoa, “The New Maximum Power Point Tracking Algorithm using ANN-Based Solar PV Systems”,IEEE TENCON,2010.
  12. Masafumi Miyatake, Mummadi Veerachary, Fuhito Toriumi Nobuhiko Fujii, Hideyoshi Ko ,” Maximum Power Point Tracking of Multiple Photovoltaic Arrays: A PSO Approach”, IEEE Transactions on Aerospace and Electronic Systems vol.47.No.1 January, 2011.
  13. J.Surya Kumari, Dr.Ch.Sai Babu, A.Kamalakar Babu, ‘Design and Analysis of P&O and IP&O MPPT Techniques for Photovoltaic System’, International Journal of Modern Engineering Research (IJMER) Vol.2, Issue.4, July-Aug, 2012.
  14. Trishan Esram,Patrick L. Chapman,’Comparison of Photovol taic Array Maximum Power Point Tracking Techniques’, IEEE Transactions on energy conversion, VOL.22,NO.2,June 2007.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2022-07-30

Issue

Volume 9, Issue 4, July-August-2022

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
K. V. Subathra "Combined Perturb and Observe and Artificial Neural Network Approach for Maximum Power Point Tracking in Photovoltaic System under Uniformly Shaded Conditions" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 4, pp.112-119, July-August-2022. Available at doi : https://doi.org/10.32628/IJSRSET2293185