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Advanced Variable Step Size Incremental Conductance MPPT for a Standalone PV System Utilizing a GA-Tuned PID Controller

Author

Listed:
  • Adeel Feroz Mirza

    (Department of Automation, University of Science and Technology of China, Hefei 230027, China)

  • Majad Mansoor

    (Department of Automation, University of Science and Technology of China, Hefei 230027, China)

  • Qiang Ling

    (Department of Automation, University of Science and Technology of China, Hefei 230027, China)

  • Muhammad Imran Khan

    (Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230027, China)

  • Omar M. Aldossary

    (Department of Physics and Astronomy, College of Science, King Saud University, PO Box 2455, Riyadh 11451, Saudi Arabia)

Abstract

In this article, a novel maximum power point tracking (MPPT) controller for the fast-changing irradiance of photovoltaic (PV) systems is introduced. Our technique utilizes a modified incremental conductance (IC) algorithm for the efficient and fast tracking of MPP. The proposed system has a simple implementation, fast tracking, and achieved steady-state oscillation. Traditional MPPT techniques use a tradeoff between steady-state and transition-state parameters. The shortfalls of various techniques are studied. A comprehensive comparative study is done to test various existing techniques against the proposed technique. The common parameters discussed in this study are fast convergence, efficiency, and reduced oscillations. The proposed method successfully addresses these issues and improves the results significantly by using a proportional integral deferential (PID) controller with a genetic algorithm (GA) to predict the variable step size of the IC-based MPPT technique. The system is designed and tested against the perturbation and observation (P&O)-based MPPT technique. Our technique effectively detects global maxima (GM) for fast-changing irradiance due to the adopted GA-based tuning of the controller. A comparative analysis of the results proves the superior performance and capabilities to track GM in fewer iterations.

Suggested Citation

  • Adeel Feroz Mirza & Majad Mansoor & Qiang Ling & Muhammad Imran Khan & Omar M. Aldossary, 2020. "Advanced Variable Step Size Incremental Conductance MPPT for a Standalone PV System Utilizing a GA-Tuned PID Controller," Energies, MDPI, vol. 13(16), pages 1-25, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4153-:d:397623
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    Cited by:

    1. Srinivasan Vadivel & Boopathi C. Sengodan & Sridhar Ramasamy & Mominul Ahsan & Julfikar Haider & Eduardo M. G. Rodrigues, 2022. "Social Grouping Algorithm Aided Maximum Power Point Tracking Scheme for Partial Shaded Photovoltaic Array," Energies, MDPI, vol. 15(6), pages 1-17, March.
    2. Kostas Bavarinos & Anastasios Dounis & Panagiotis Kofinas, 2021. "Maximum Power Point Tracking Based on Reinforcement Learning Using Evolutionary Optimization Algorithms," Energies, MDPI, vol. 14(2), pages 1-23, January.
    3. Muhammad Mateen Afzal Awan & Aamer Bilal Asghar & Muhammad Yaqoob Javed & Zsolt Conka, 2023. "Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    4. Ahmad Taher Azar & Azher M. Abed & Farah Ayad Abdulmajeed & Ibrahim A. Hameed & Nashwa Ahmad Kamal & Anwar Jaafar Mohamad Jawad & Ali Hashim Abbas & Zainab Abdulateef Rashed & Zahraa Sabah Hashim & Mo, 2022. "A New Nonlinear Controller for the Maximum Power Point Tracking of Photovoltaic Systems in Micro Grid Applications Based on Modified Anti-Disturbance Compensation," Sustainability, MDPI, vol. 14(17), pages 1-25, August.
    5. Mirza, Adeel Feroz & Mansoor, Majad & Zhan, Keyu & Ling, Qiang, 2021. "High-efficiency swarm intelligent maximum power point tracking control techniques for varying temperature and irradiance," Energy, Elsevier, vol. 228(C).
    6. Muhammad Mateen Afzal Awan & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Krzysztof Ejsmont, 2022. "Performance Optimization of a Ten Check MPPT Algorithm for an Off-Grid Solar Photovoltaic System," Energies, MDPI, vol. 15(6), pages 1-31, March.
    7. Omer Saleem & Shehryaar Ali & Jamshed Iqbal, 2023. "Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller," Energies, MDPI, vol. 16(13), pages 1-20, June.

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