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Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions Using Bat Algorithm

Author

Listed:
  • Mehdi Seyedmahmoudian

    (School of Software and Electrical Engineering, Swinburne University of Technology, Victoria, VIC 3122, Australia)

  • Tey Kok Soon

    (Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia)

  • Elmira Jamei

    (College of Engineering and Science, Victoria University, Victoria, VIC 3011, Australia)

  • Gokul Sidarth Thirunavukkarasu

    (School of Engineering, Deakin University, Victoria, VIC 3216, Australia)

  • Ben Horan

    (School of Engineering, Deakin University, Victoria, VIC 3216, Australia)

  • Saad Mekhilef

    (Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Alex Stojcevski

    (School of Software and Electrical Engineering, Swinburne University of Technology, Victoria, VIC 3122, Australia)

Abstract

The vibrant, noiseless, and low-maintenance characteristics of photovoltaic (PV) systems make them one of the fast-growing technologies in the modern era. This on-demand source of energy suffers from low-output efficiency compared with other alternatives. Given that PV systems must be installed in outdoor spaces, their efficiency is significantly affected by the inevitable complication called partial shading (PS). Partial shading occurs when different sections of the solar array are subjected to different levels of solar irradiance, which then leads to a multiple-peak function in the output characteristics of the system. Conventional tracking techniques, along with some nascent/novel approaches used for the tracking maximum power point (MPP), are unsatisfactory when subjected to PS, eventually leading to the reduced efficiency of the PV system. This study aims at investigating the use of the bat algorithm (BA), a nature-inspired metaheuristic algorithm for MPP tracking (MPPT) subjected to PS conditions. A brief explanation of the behavior of the PV system under the PS condition and the advantages of using BA for estimating the MPPT of the PV system under PS condition is discussed. The deployment of the BA for the MPPT in PV systems is then explained in detail highlighting the simulation results which verifies whether the proposed method is faster, more efficient, sustainable and more reliable than conventional and other soft computing-based methods. Three testing conditions are considered in the simulation, and the results indicate that the proposed technique has high efficiency and reliability even when subjected to an acute shading condition.

Suggested Citation

  • Mehdi Seyedmahmoudian & Tey Kok Soon & Elmira Jamei & Gokul Sidarth Thirunavukkarasu & Ben Horan & Saad Mekhilef & Alex Stojcevski, 2018. "Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions Using Bat Algorithm," Sustainability, MDPI, vol. 10(5), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1347-:d:143356
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    References listed on IDEAS

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    1. Sharma, Naveen & Varun, & Siddhartha,, 2012. "Stochastic techniques used for optimization in solar systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1399-1411.
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    Cited by:

    1. Morsali, Roozbeh & Thirunavukkarasu, Gokul Sidarth & Seyedmahmoudian, Mehdi & Stojcevski, Alex & Kowalczyk, Ryszard, 2020. "A relaxed constrained decentralised demand side management system of a community-based residential microgrid with realistic appliance models," Applied Energy, Elsevier, vol. 277(C).
    2. Dalia Yousri & Thanikanti Sudhakar Babu & Dalia Allam & Vigna. K. Ramachandaramurthy & Eman Beshr & Magdy. B. Eteiba, 2019. "Fractional Chaos Maps with Flower Pollination Algorithm for Partial Shading Mitigation of Photovoltaic Systems," Energies, MDPI, vol. 12(18), pages 1-27, September.
    3. Mehdi Seyedmahmoudian & Gokul Sidarth Thirunavukkarasu & Elmira Jamei & Tey Kok Soon & Ben Horan & Saad Mekhilef & Alex Stojcevski, 2020. "A Sustainable Distributed Building Integrated Photo-Voltaic System Architecture with a Single Radial Movement Optimization Based MPPT Controller," Sustainability, MDPI, vol. 12(16), pages 1-21, August.
    4. Ghaeth Fandi & Vladimír Krepl & Ibrahim Ahmad & Famous O. Igbinovia & Tatiana Ivanova & Soliman Fandie & Zdenek Muller & Josef Tlusty, 2018. "Design of an Emergency Energy System for a City Assisted by Renewable Energy, Case Study: Latakia, Syria," Energies, MDPI, vol. 11(11), pages 1-22, November.
    5. Mehdi Seyedmahmoudian & Elmira Jamei & Gokul Sidarth Thirunavukkarasu & Tey Kok Soon & Michael Mortimer & Ben Horan & Alex Stojcevski & Saad Mekhilef, 2018. "Short-Term Forecasting of the Output Power of a Building-Integrated Photovoltaic System Using a Metaheuristic Approach," Energies, MDPI, vol. 11(5), pages 1-23, May.
    6. Zixia Yuan & Guojiang Xiong & Xiaofan Fu, 2022. "Artificial Neural Network for Fault Diagnosis of Solar Photovoltaic Systems: A Survey," Energies, MDPI, vol. 15(22), pages 1-18, November.
    7. Mostafa Bakkar & Ahmed Aboelhassan & Mostafa Abdelgeliel & Michael Galea, 2021. "PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions," Energies, MDPI, vol. 14(4), pages 1-20, February.
    8. Areeba Naqvi & Ahsan Ali & Wael A. Altabey & Sallam A. Kouritem, 2022. "Energy Harvesting from Fluid Flow Using Piezoelectric Materials: A Review," Energies, MDPI, vol. 15(19), pages 1-35, October.
    9. Catalina González-Castaño & James Marulanda & Carlos Restrepo & Samir Kouro & Alfonso Alzate & Jose Rodriguez, 2021. "Hardware-in-the-Loop to Test an MPPT Technique of Solar Photovoltaic System: A Support Vector Machine Approach," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    10. Hossam Hassan Ammar & Ahmad Taher Azar & Raafat Shalaby & M. I. Mahmoud, 2019. "Metaheuristic Optimization of Fractional Order Incremental Conductance (FO-INC) Maximum Power Point Tracking (MPPT)," Complexity, Hindawi, vol. 2019, pages 1-13, November.

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