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Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method

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  • Dileep, G.
  • Singh, S.N.

Abstract

Solar energy is one of the important renewable energy resources as it is pollution free, clean, never-ending and abundant. Solar photovoltaic technologies are mounting vigor attention in the modern electrical power applications due to fast growth in the relative sectors of semiconductor and power electronics. It is significant to operate solar photovoltaic energy conversion systems to its maximum power output to raise the efficiency. Maximum power point tracking plays a very important role for extracting maximum power from the solar photovoltaic module and transferring that power to the load. The present work highlights a survey on perturb and observe method maximum power point tracking technique for solar photovoltaic system undertaken by considering the various works already listed relative study has been carried out, which includes different perturb and observe method on maximum power point tracking techniques and draw their advantages and drawbacks. These techniques vary in many aspects, which can be broadly categorized on the basis of simplicity, way of implementing, type of sensors, total cost of the system, range of effectiveness, hardware requirement and speed of convergence. It is expected that this review work will provide precious information for solar photovoltaic professionals to keep alongside with the latest progress in this area, as well as for new researchers to get started on maximum power point tracking.

Suggested Citation

  • Dileep, G. & Singh, S.N., 2015. "Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 109-129.
    • Handle: RePEc:eee:rensus:v:50:y:2015:i:c:p:109-129
    DOI: 10.1016/j.rser.2015.04.072
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    Cited by:

    1. 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.
    2. Marwa Hassan & Alsnosy Balbaa & Hanady H. Issa & Noha H. El-Amary, 2018. "Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator," Energies, MDPI, vol. 11(10), pages 1-25, October.
    3. Joshi, Puneet & Arora, Sudha, 2017. "Maximum power point tracking methodologies for solar PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1154-1177.
    4. Çelik, Özgür & Teke, Ahmet & Tan, Adnan, 2018. "Overview of micro-inverters as a challenging technology in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3191-3206.
    5. Li, Qiyu & Zhao, Shengdun & Wang, Mengqi & Zou, Zhongyue & Wang, Bin & Chen, Qixu, 2017. "An improved perturbation and observation maximum power point tracking algorithm based on a PV module four-parameter model for higher efficiency," Applied Energy, Elsevier, vol. 195(C), pages 523-537.
    6. 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.
    7. Kota, Venkata Reddy & Bhukya, Muralidhar Nayak, 2017. "A novel linear tangents based P&O scheme for MPPT of a PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 257-267.
    8. T. Nagadurga & P. V. R. L. Narasimham & V. S. Vakula, 2021. "Global Maximum Power Point Tracking of Solar Photovoltaic Strings under Partial Shading Conditions Using Cat Swarm Optimization Technique," Sustainability, MDPI, vol. 13(19), pages 1-20, October.
    9. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "Comparisons of MPPT performances of isolated and non-isolated DC–DC converters by using a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1100-1113.
    10. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    11. Tingting Cai & Sutong Liu & Gangui Yan & Hongbo Liu, 2019. "Analysis of Doubly Fed Induction Generators Participating in Continuous Frequency Regulation with Different Wind Speeds Considering Regulation Power Constraints," Energies, MDPI, vol. 12(4), pages 1-20, February.
    12. Kermadi, Mostefa & Berkouk, El Madjid, 2017. "Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 369-386.

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