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A new adaptive MPPT technique using an improved INC algorithm supported by fuzzy self-tuning controller for a grid-linked photovoltaic system

Author

Listed:
  • Nagwa F Ibrahim
  • Mohamed Metwally Mahmoud
  • Hashim Alnami
  • Daniel Eutyche Mbadjoun Wapet
  • Sid Ahmed El Mehdi Ardjoun
  • Mohamed I Mosaad
  • Ammar M Hassan
  • H Abdelfattah

Abstract

Solar energy, a prominent renewable resource, relies on photovoltaic systems (PVS) to capture energy efficiently. The challenge lies in maximizing power generation, which fluctuates due to changing environmental conditions like irradiance and temperature. Maximum Power Point Tracking (MPPT) techniques have been developed to optimize PVS output. Among these, the incremental conductance (INC) method is widely recognized. However, adapting INC to varying environmental conditions remains a challenge. This study introduces an innovative approach to adaptive MPPT for grid-connected PVS, enhancing classical INC by integrating a PID controller updated through a fuzzy self-tuning controller (INC-FST). INC-FST dynamically regulates the boost converter signal, connecting the PVS’s DC output to the grid-connected inverter. A comprehensive evaluation, comparing the proposed adaptive MPPT technique (INC-FST) with conventional MPPT methods such as INC, Perturb & Observe (P&O), and INC Fuzzy Logic (INC-FL), was conducted. Metrics assessed include current, voltage, efficiency, power, and DC bus voltage under different climate scenarios. The proposed MPPT-INC-FST algorithm demonstrated superior efficiency, achieving 99.80%, 99.76%, and 99.73% for three distinct climate scenarios. Furthermore, the comparative analysis highlighted its precision in terms of control indices, minimizing overshoot, reducing rise time, and maximizing PVS power output.

Suggested Citation

  • Nagwa F Ibrahim & Mohamed Metwally Mahmoud & Hashim Alnami & Daniel Eutyche Mbadjoun Wapet & Sid Ahmed El Mehdi Ardjoun & Mohamed I Mosaad & Ammar M Hassan & H Abdelfattah, 2023. "A new adaptive MPPT technique using an improved INC algorithm supported by fuzzy self-tuning controller for a grid-linked photovoltaic system," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-22, November.
    • Handle: RePEc:plo:pone00:0293613
    DOI: 10.1371/journal.pone.0293613
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    References listed on IDEAS

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    1. Sampath Kumar Vankadara & Shamik Chatterjee & Praveen Kumar Balachandran, 2022. "An accurate analytical modeling of solar photovoltaic system considering Rs and Rsh under partial shaded condition," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2472-2481, October.
    2. Piotr Bórawski & Aneta Bełdycka-Bórawska & Lisa Holden & Tomasz Rokicki, 2022. "The Role of Renewable Energy Sources in Electricity Production in Poland and the Background of Energy Policy of the European Union at the Beginning of the COVID-19 Crisis," Energies, MDPI, vol. 15(22), pages 1-17, November.
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