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An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions

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  • Ali M. Eltamaly

    (Sustainable Energy Technologies Center, King Saud University, Riyadh 11421, Saudi Arabia
    Electrical Engineering Department, Mansoura University, Mansoura 35516, Egypt
    K.A. CARE Energy Research and Innovation Center, Riyadh 11451, Saudi Arabia)

Abstract

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage ( P–V ) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.

Suggested Citation

  • Ali M. Eltamaly, 2021. "An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(4), pages 1-26, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:953-:d:497753
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    References listed on IDEAS

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    1. Ali M. Eltamaly & Hassan M. H. Farh & Mamdooh S. Al Saud, 2019. "Impact of PSO Reinitialization on the Accuracy of Dynamic Global Maximum Power Detection of Variant Partially Shaded PV Systems," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
    2. Ali M. Eltamaly & M. S. Al-Saud & A. G. Abo-Khalil, 2020. "Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy," Sustainability, MDPI, vol. 12(3), pages 1-20, February.
    3. Ali M. Eltamaly, 2021. "A Novel Strategy for Optimal PSO Control Parameters Determination for PV Energy Systems," Sustainability, MDPI, vol. 13(2), pages 1-28, January.
    4. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
    5. Eltamaly, Ali M. & Al-Saud, M.S. & Abokhalil, Ahmed G. & Farh, Hassan M.H., 2020. "Simulation and experimental validation of fast adaptive particle swarm optimization strategy for photovoltaic global peak tracker under dynamic partial shading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
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    Cited by:

    1. Elmamoune Halassa & Lakhdar Mazouz & Abdellatif Seghiour & Aissa Chouder & Santiago Silvestre, 2023. "Revolutionizing Photovoltaic Systems: An Innovative Approach to Maximum Power Point Tracking Using Enhanced Dandelion Optimizer in Partial Shading Conditions," Energies, MDPI, vol. 16(9), pages 1-23, April.
    2. Majed A. Alotaibi & Ali M. Eltamaly, 2021. "A Smart Strategy for Sizing of Hybrid Renewable Energy System to Supply Remote Loads in Saudi Arabia," Energies, MDPI, vol. 14(21), pages 1-24, October.
    3. Khizer Mehmood & Naveed Ishtiaq Chaudhary & Zeshan Aslam Khan & Khalid Mehmood Cheema & Muhammad Asif Zahoor Raja & Ahmad H. Milyani & Abdullah Ahmed Azhari, 2022. "Dwarf Mongoose Optimization Metaheuristics for Autoregressive Exogenous Model Identification," Mathematics, MDPI, vol. 10(20), pages 1-21, October.
    4. Tabassum Kanwal & Saif Ur Rehman & Tariq Ali & Khalid Mahmood & Santos Gracia Villar & Luis Alonso Dzul Lopez & Imran Ashraf, 2023. "An Intelligent Dual-Axis Solar Tracking System for Remote Weather Monitoring in the Agricultural Field," Agriculture, MDPI, vol. 13(8), pages 1-19, August.
    5. Timmidi Nagadurga & Pasumarthi Venkata Ramana Lakshmi Narasimham & V. S. Vakula & Ramesh Devarapalli & Fausto Pedro García Márquez, 2021. "Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm," Energies, MDPI, vol. 14(14), pages 1-23, July.
    6. Ahmed Samawi Alkhafaji & Hafedh Trabelsi, 2022. "Uses of Superconducting Magnetic Energy Storage Systems in Microgrids under Unbalanced Inductive Loads and Partial Shading Conditions," Energies, MDPI, vol. 15(22), pages 1-28, November.
    7. Majed A. Alotaibi & Ali M. Eltamaly, 2022. "Upgrading Conventional Power System for Accommodating Electric Vehicle through Demand Side Management and V2G Concepts," Energies, MDPI, vol. 15(18), pages 1-27, September.
    8. Tiago H. de A. Mateus & José A. Pomilio & Ruben B. Godoy & João O. P. Pinto, 2022. "VSG Control Applied to Seven-Level PV Inverter for Partial Shading Impact Abatement," Energies, MDPI, vol. 15(17), pages 1-14, September.
    9. Weng-Hooi Tan & Junita Mohamad-Saleh, 2023. "Critical Review on Interrelationship of Electro-Devices in PV Solar Systems with Their Evolution and Future Prospects for MPPT Applications," Energies, MDPI, vol. 16(2), pages 1-37, January.
    10. Sy Ngo & Chian-Song Chiu & Thanh-Dong Ngo, 2022. "A Novel Horse Racing Algorithm Based MPPT Control for Standalone PV Power Systems," Energies, MDPI, vol. 15(20), pages 1-18, October.
    11. Zahra Bel Hadj Salah & Saber Krim & Mohamed Ali Hajjaji & Badr M. Alshammari & Khalid Alqunun & Ahmed Alzamil & Tawfik Guesmi, 2023. "A New Efficient Cuckoo Search MPPT Algorithm Based on a Super-Twisting Sliding Mode Controller for Partially Shaded Standalone Photovoltaic System," Sustainability, MDPI, vol. 15(12), pages 1-38, June.
    12. Srinivasan Alwar & Devakirubakaran Samithas & Meenakshi Sundaram Boominathan & Praveen Kumar Balachandran & Lucian Mihet-Popa, 2022. "Performance Analysis of Thermal Image Processing-Based Photovoltaic Fault Detection and PV Array Reconfiguration—A Detailed Experimentation," Energies, MDPI, vol. 15(22), pages 1-21, November.
    13. Muhannad Alaraj & Astitva Kumar & Ibrahim Alsaidan & Mohammad Rizwan & Majid Jamil, 2022. "An Advanced and Robust Approach to Maximize Solar Photovoltaic Power Production," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    14. Ali M. Eltamaly & Zeyad A. Almutairi & Mohamed A. Abdelhamid, 2023. "Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems," Energies, MDPI, vol. 16(13), pages 1-22, July.
    15. Ali Abedaljabar Al-Samawi & Hafedh Trabelsi, 2022. "New Nine-Level Cascade Multilevel Inverter with a Minimum Number of Switches for PV Systems," Energies, MDPI, vol. 15(16), pages 1-25, August.
    16. Eltamaly, Ali M., 2021. "A novel musical chairs algorithm applied for MPPT of PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    17. Haoming Liu & Muhammad Yasir Ali Khan & Xiaoling Yuan, 2023. "Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review," Energies, MDPI, vol. 16(15), pages 1-64, July.
    18. Mpho Sam Nkambule & Ali N. Hasan & Ahmed Ali & Thokozani Shongwe, 2022. "A Novel Control Strategy in Grid-Integrated Photovoltaic System for Power Quality Enhancement," Energies, MDPI, vol. 15(15), pages 1-31, August.
    19. Ehab Mohamed Ali & Ahmed K. Abdelsalam & Karim H. Youssef & Ahmed A. Hossam-Eldin, 2021. "An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions," Energies, MDPI, vol. 14(21), pages 1-21, November.

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