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A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions

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  • Belhachat, Faiza
  • Larbes, Cherif

Abstract

Maximum power point tracking (MPPT) control techniques play a vital role in efficiency improvement of photovoltaic (PV) systems. It is mainly used to extract maximum possible power of the PV modules under both variable climatic and partial shaded condition (PSC). From literature, various types of MPPT techniques have been developed to track the maximum power point efficiently, ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and drawbacks.

Suggested Citation

  • Belhachat, Faiza & Larbes, Cherif, 2018. "A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 513-553.
    • Handle: RePEc:eee:rensus:v:92:y:2018:i:c:p:513-553
    DOI: 10.1016/j.rser.2018.04.094
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    Citations

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    Cited by:

    1. 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.
    2. Yinxiao Zhu & Moon Keun Kim & Huiqing Wen, 2018. "Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics," Energies, MDPI, vol. 12(1), pages 1-20, December.
    3. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    4. Moreira, Hugo Soeiro & Lucas de Souza Silva, João & Gomes dos Reis, Marcos Vinicios & de Bastos Mesquita, Daniel & Kikumoto de Paula, Bruno Henrique & Villalva, Marcelo Gradella, 2021. "Experimental comparative study of photovoltaic models for uniform and partially shading conditions," Renewable Energy, Elsevier, vol. 164(C), pages 58-73.
    5. Kamran Ali Khan Niazi & Yongheng Yang & Tamas Kerekes & Dezso Sera, 2021. "A Simple Mismatch Mitigating Partial Power Processing Converter for Solar PV Modules," Energies, MDPI, vol. 14(8), pages 1-18, April.
    6. Yu-Pei Huang & Cheng-En Ye & Xiang Chen, 2018. "A Modified Firefly Algorithm with Rapid Response Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions," Energies, MDPI, vol. 11(9), pages 1-33, August.
    7. Maria I. S. Guerra & Fábio M. Ugulino de Araújo & Mahmoud Dhimish & Romênia G. Vieira, 2021. "Assessing Maximum Power Point Tracking Intelligent Techniques on a PV System with a Buck–Boost Converter," Energies, MDPI, vol. 14(22), pages 1-21, November.
    8. Ali Bughneda & Mohamed Salem & Anna Richelli & Dahaman Ishak & Salah Alatai, 2021. "Review of Multilevel Inverters for PV Energy System Applications," Energies, MDPI, vol. 14(6), pages 1-23, March.
    9. Waleed Al Abri & Rashid Al Abri & Hassan Yousef & Amer Al-Hinai, 2021. "A Simple Method for Detecting Partial Shading in PV Systems," Energies, MDPI, vol. 14(16), pages 1-12, August.
    10. Luo, Yongqiang & Zhang, Ling & Liu, Zhongbing & Yu, Jinghua & Xu, Xinhua & Su, Xiaosong, 2020. "Towards net zero energy building: The application potential and adaptability of photovoltaic-thermoelectric-battery wall system," Applied Energy, Elsevier, vol. 258(C).
    11. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    12. Zain Ahmad Khan & Laiq Khan & Saghir Ahmad & Sidra Mumtaz & Muhammad Jafar & Qudrat Khan, 2021. "RBF neural network based backstepping terminal sliding mode MPPT control technique for PV system," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-23, April.
    13. Shaowu Li, 2021. "Circuit Parameter Range of Photovoltaic System to Correctly Use the MPP Linear Model of Photovoltaic Cell," Energies, MDPI, vol. 14(13), pages 1-27, July.
    14. Wang, Shuoqi & Lu, Languang & Han, Xuebing & Ouyang, Minggao & Feng, Xuning, 2020. "Virtual-battery based droop control and energy storage system size optimization of a DC microgrid for electric vehicle fast charging station," Applied Energy, Elsevier, vol. 259(C).
    15. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    16. Carlos Andres Ramos-Paja & Daniel Gonzalez Montoya & Juan David Bastidas-Rodriguez, 2018. "Sliding-Mode Control of Distributed Maximum Power Point Tracking Converters Featuring Overvoltage Protection," Energies, MDPI, vol. 11(9), pages 1-40, August.
    17. Yadav, Anurag Singh & Mukherjee, V., 2021. "Conventional and advanced PV array configurations to extract maximum power under partial shading conditions: A review," Renewable Energy, Elsevier, vol. 178(C), pages 977-1005.
    18. 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.

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