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A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions

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  • Rezk, Hegazy
  • Fathy, Ahmed
  • Abdelaziz, Almoataz Y.

Abstract

The characteristics of photovoltaic array under partial shading comprises multiple local MPPs and one global. The classical maximum power point tracking (MPPT) algorithms can’t reach to global MPP. Accordingly, this work aims to study the behavior performance of two optimization techniques. They have been developed for extracting the global MPP from the partially shaded PVPS. The two studied techniques include Particle Swarm Optimization (PSO) and Cuckoo Search (CS). A comprehensive assessment of the two techniques has been carried out against a conventional algorithm of INR−based tracker. The tracking performances of PSO and CS based trackers are evaluated for different partial shading patterns based on MATLAB software. Results confirm that PSO and CS based trackers guarantee the convergence to the global MPP. Furthermore, they have the best performance in comparison with the conventional one. Additionally; the obtained results show that the CS−based tracker has superiority compared with PSO. The tracking time in case of CS−tracker is reduced compared to PSO in all the studied cases.

Suggested Citation

  • Rezk, Hegazy & Fathy, Ahmed & Abdelaziz, Almoataz Y., 2017. "A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 377-386.
    • Handle: RePEc:eee:rensus:v:74:y:2017:i:c:p:377-386
    DOI: 10.1016/j.rser.2017.02.051
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    2. Fahd A. Alturki & Abdullrahman A. Al-Shamma’a & Hassan M. H. Farh, 2020. "Simulations and dSPACE Real-Time Implementation of Photovoltaic Global Maximum Power Extraction under Partial Shading," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    3. J. C. Teo & Rodney H. G. Tan & V. H. Mok & Vigna K. Ramachandaramurthy & ChiaKwang Tan, 2018. "Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String," Energies, MDPI, vol. 11(7), pages 1-22, July.
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    5. Ahmad Dawahdeh & Hussein Sharadga & Sunil Kumar, 2024. "Novel MPPT Controller Augmented with Neural Network for Use with Photovoltaic Systems Experiencing Rapid Solar Radiation Changes," Sustainability, MDPI, vol. 16(3), pages 1-22, January.
    6. Hegazy Rezk & Ziad Mohammed Ali & Omer Abdalla & Obai Younis & Mohamed Ramadan Gomaa & Mauia Hashim, 2019. "Hybrid Moth-Flame Optimization Algorithm and Incremental Conductance for Tracking Maximum Power of Solar PV/Thermoelectric System under Different Conditions," Mathematics, MDPI, vol. 7(10), pages 1-21, September.
    7. Pal, Rudra Sankar & Mukherjee, V., 2020. "Metaheuristic based comparative MPPT methods for photovoltaic technology under partial shading condition," Energy, Elsevier, vol. 212(C).
    8. Isabel Santiago & David Trillo Montero & Juan J. Luna Rodríguez & Isabel M. Moreno Garcia & Emilio J. Palacios Garcia, 2017. "Graphical Diagnosis of Performances in Photovoltaic Systems: A Case Study in Southern Spain," Energies, MDPI, vol. 10(12), pages 1-26, November.
    9. Camilo, Jones C. & Guedes, Tatiana & Fernandes, Darlan A. & Melo, J.D. & Costa, F.F. & Sguarezi Filho, Alfeu J., 2019. "A maximum power point tracking for photovoltaic systems based on Monod equation," Renewable Energy, Elsevier, vol. 130(C), pages 428-438.
    10. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    11. Jouda Arfaoui & Hegazy Rezk & Mujahed Al-Dhaifallah & Feki Elyes & Mami Abdelkader, 2019. "Numerical Performance Evaluation of Solar Photovoltaic Water Pumping System under Partial Shading Condition using Modern Optimization," Mathematics, MDPI, vol. 7(11), pages 1-18, November.
    12. Peng, Lele & Zheng, Shubin & Chai, Xiaodong & Li, Liming, 2018. "A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances," Applied Energy, Elsevier, vol. 210(C), pages 303-316.
    13. Mohamed, Mohamed A. & Zaki Diab, Ahmed A. & Rezk, Hegazy, 2019. "Partial shading mitigation of PV systems via different meta-heuristic techniques," Renewable Energy, Elsevier, vol. 130(C), pages 1159-1175.
    14. Lappalainen, Kari & Valkealahti, Seppo, 2020. "Number of maximum power points in photovoltaic arrays during partial shading events by clouds," Renewable Energy, Elsevier, vol. 152(C), pages 812-822.
    15. Alfredo Gil-Velasco & Carlos Aguilar-Castillo, 2021. "A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(9), pages 1-12, April.
    16. Nassef, Ahmed M. & Olabi, A.G. & Rodriguez, Cristina & Abdelkareem, Mohammad Ali & Rezk, Hegazy, 2021. "Optimal operating parameter determination and modeling to enhance methane production from macroalgae," Renewable Energy, Elsevier, vol. 163(C), pages 2190-2197.
    17. Zhang, Xiaoshun & Li, Shengnan & He, Tingyi & Yang, Bo & Yu, Tao & Li, Haofei & Jiang, Lin & Sun, Liming, 2019. "Memetic reinforcement learning based maximum power point tracking design for PV systems under partial shading condition," Energy, Elsevier, vol. 174(C), pages 1079-1090.
    18. Memon, Mudasir Ahmed & Mekhilef, Saad & Mubin, Marizan & Aamir, Muhammad, 2018. "Selective harmonic elimination in inverters using bio-inspired intelligent algorithms for renewable energy conversion applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2235-2253.

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