Improving the Maximum Power Point Tracking in a Photovoltaic System Based on the Resistance-Predictive Method

Document Type : Research article

Authors

1 Khuzestan Regional Electric Company, Ahvaz, Iran.

2 Faculty of Electrical Engineering, Amirkabir University of Technology (Tehran polytechnic), Tehran, Iran.

3 Department of Electrical Engineering, Islamic Azad University of Tehran, Tehran, Iran.

4 Department of Electrical Engineering, Naghshejahan Institute of Higher Education, Baharestan, Isfahan, Iran.

Abstract
An established technique to maximize the output power of photovoltaic (PV) systems, thereby raising ‎the efficiency of renewable energy systems, is maximum power point tracking (MPPT). This paper ‎focuses on designing and controlling a boost converter for MPPT in a PV system to calculate the ‎appropriate range of output resistance, minimum inductance, input capacitor, and output capacitor for ‎the boost converter so that the maximum PV output is achieved and the decision speed of MOSFET ‎switching is obtained by adopting the combined resistance-predictive method. The simulation results ‎demonstrate the efficacy of the proposed method in attaining these objectives. The suggested technique ‎can effectively track the maximum power point (MPP) within a broad spectrum of solar radiation while ‎ensuring that the duty cycle remains within its permissible range.‎

Graphical Abstract

Improving the Maximum Power Point Tracking in a Photovoltaic System Based on the Resistance-Predictive Method

Highlights

 

  • Enhancing the MPPT by designing and controlling the step-up converter of the PV system
  • Ensuring an efficient MPPT by proper calculation of parameters
  • Employing predictive control to enhance the speed of MOSFET switching decisions
  • Implementing a resistive-predictive step-up converter control

Keywords


 

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, have been completely observed by the authors.

 

Credit Authorship Contribution Statement

Moaiad Mohseni: Conceptualization, Formal analysis, Project administration, Supervision, Validation, Roles/Writing - original draft. Alireza Niknam Kumleh: Conceptualization, Investigation, Methodology, Resources, Visualization, Writing - review & editing. Mehdi Alibakhshi: Methodology, Resources, Software, Supervision, Validation. Mona Sheikhi Abou Masoudi: Funding acquisition, Investigation, Writing-review & editing.

 

Bibliography

Moaiad Mohseni was born in Kwait. He received his B.SC Degree in Electrical Engineering, Kazeroon Branch, Islamic Azad University, Kazeroon, Iran in 2001, and his M.S. and Ph.D. degrees in Electrical Engineering from Dezful Branch, Islamic Azad University, Dezful, Iran, in 2011and 2021, respectively. His Research Include Power Market and Smart Grid and renewable energy systems.

Alireza Niknam Kumleh was born in Tehran. He received his B.SC Degree in Electrical Engineering, Faculty of Electrical Engineering, Amirkabir University of Technology (Tehran polytechnic), Tehran, Iran in 2012, and his M.S. degrees in Electrical Engineering from Faculty of Electrical Engineering, Amirkabir University of Technology (Tehran polytechnic), Tehran, Iran in 2015, respectively. His Research Include Power Market, Smart Grid, renewable energy systems.

Mehdi Alibakhshi was born in Iran in 1985. She received his Master degree in control engineering from south Tehran Branch, Islamic Azad University, Tehran, Iran, in 2011. He currently works as a researcher. Also, he has taught for ten years at Borujerd Islamic Azad University. he has published one research papers, one conference papers. His research interests include power electronic, predictive control, and microgrids.

Mona Sheikhi Abou Masoudi was born in Iran in 1986. She received his Master degree in Electronic Engineering from Oloom Tahghighat Branch, Islamic Azad University, Tehran, Iran, in 2011. She currently works as a teacher in Naghshe Jahan institute. Also, she has taught for ten years at Sepahan and Safahan and Kharazmi university. She has published two research papers, one conference papers. Her research interests include power electronic, control, and microgrids.

 

Citation

M. Mohseni, A. Niknam Kumleh, M. Alibakhshi, and M. Sheikhi Abou Masoudi, "Improving the Maximum Power Point Tracking in a Photovoltaic System ‎Based on the Resistance-Predictive Method," Journal of Green Energy Research and Innovation, vol. 1, no. 2, pp. 81-102, 2024.

 

 
 
Volume 1, Issue 2
Spring 2024
Pages 81-102

  • Receive Date 27 January 2024
  • Revise Date 27 February 2024
  • Accept Date 01 March 2024
  • Publish Date 01 June 2024