IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i5p1347-d143356.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/5/1347/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/5/1347/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhsen, Dhiaa Halboot & Khatib, Tamer & Nagi, Farrukh, 2017. "A review of photovoltaic water pumping system designing methods, control strategies and field performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 70-86.
    2. Al-Sulttani, Ali O. & Ahsan, Amimul & Hanoon, Ammar N. & Rahman, A. & Daud, N.N.N. & Idrus, S., 2017. "Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique," Applied Energy, Elsevier, vol. 203(C), pages 280-303.
    3. Amani, Madjid & Ghenaiet, Adel, 2020. "Novel hybridization of solar central receiver system with combined cycle power plant," Energy, Elsevier, vol. 201(C).
    4. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2013. "A review of photovoltaic systems size optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 454-465.
    5. Conroy, Tim & Collins, Maurice N. & Fisher, James & Grimes, Ronan, 2018. "Thermal and mechanical analysis of a sodium-cooled solar receiver operating under a novel heliostat aiming point strategy," Applied Energy, Elsevier, vol. 230(C), pages 590-614.
    6. Behar, Omar & Khellaf, Abdallah & Mohammedi, Kamal & Ait-Kaci, Sabrina, 2014. "A review of integrated solar combined cycle system (ISCCS) with a parabolic trough technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 223-250.
    7. Neha Gupta & Mohini Agarwal & Pratibha Garg & Manoj Bansal, 2021. "Revenue optimization modeling for renewable energy resource mix for sustainable development," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(2), pages 108-115, April.
    8. Yu, Qiang & Li, Zihao & Zhao, Wenyao & Zhang, Gaocheng & Xiong, Xinyu & Wu, Zhiyong, 2024. "Modeling and control strategy optimizing of solar flux distribution in a four quadrant and adjustable focusing solar furnace," Applied Energy, Elsevier, vol. 363(C).
    9. Araya, R. & Bustos, F. & Contreras, J. & Fuentes, A., 2017. "Life-cycle savings for a flat-plate solar water collector plant in Chile," Renewable Energy, Elsevier, vol. 112(C), pages 365-377.
    10. Dominković, D.F. & Weinand, J.M. & Scheller, F. & D'Andrea, M. & McKenna, R., 2022. "Reviewing two decades of energy system analysis with bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    11. Luigi Cirocco & Martin Belusko & Frank Bruno & John Boland & Peter Pudney, 2014. "Optimisation of Storage for Concentrated Solar Power Plants," Challenges, MDPI, vol. 5(2), pages 1-31, December.
    12. Ciller, Pedro & Lumbreras, Sara, 2020. "Electricity for all: The contribution of large-scale planning tools to the energy-access problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    13. Lizárraga-Morazán, Juan Ramón & Picón-Núñez, Martín, 2023. "Optimal sizing and control strategy of low temperature solar thermal utility systems," Energy, Elsevier, vol. 263(PC).
    14. Voyant, Cyril & Paoli, Christophe & Muselli, Marc & Nivet, Marie-Laure, 2013. "Multi-horizon solar radiation forecasting for Mediterranean locations using time series models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 44-52.
    15. Azadian, Farshad & Radzi, M.A.M., 2013. "A general approach toward building integrated photovoltaic systems and its implementation barriers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 527-538.
    16. Cheng, Ze-Dong & Zhao, Xue-Ru & He, Ya-Ling, 2018. "Novel optical efficiency formulas for parabolic trough solar collectors: Computing method and applications," Applied Energy, Elsevier, vol. 224(C), pages 682-697.
    17. Yan, Jian & Peng, You-duo & Cheng, Zi-ran, 2018. "Optimization of a discrete dish concentrator for uniform flux distribution on the cavity receiver of solar concentrator system," Renewable Energy, Elsevier, vol. 129(PA), pages 431-445.
    18. Cheng, Ze-Dong & He, Ya-Ling & Du, Bao-Cun & Wang, Kun & Liang, Qi, 2015. "Geometric optimization on optical performance of parabolic trough solar collector systems using particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 148(C), pages 282-293.
    19. Iqbal, M. & Azam, M. & Naeem, M. & Khwaja, A.S. & Anpalagan, A., 2014. "Optimization classification, algorithms and tools for renewable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 640-654.
    20. Ajdad, H. & Filali Baba, Y. & Al Mers, A. & Merroun, O. & Bouatem, A. & Boutammachte, N., 2019. "Particle swarm optimization algorithm for optical-geometric optimization of linear fresnel solar concentrators," Renewable Energy, Elsevier, vol. 130(C), pages 992-1001.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1347-:d:143356. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.