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MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions

Author

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  • Mohanty, Parimita
  • Bhuvaneswari, G.
  • Balasubramanian, R.
  • Dhaliwal, Navdeep Kaur

Abstract

Although solar photovoltaic technology is one of the matured technologies, its initial high cost and low efficiency have not made it fully attractive as an alternative option for electricity users. Hence it is very critical to utilize the maximum available solar power of the array and to operate the PV array at its highest energy conversion output. For this, the solar PV generating system has to operate at the maximum power output point. Since the maximum power point varies with radiation and temperature, it is difficult to maintain optimum power operation at all radiation levels. Over the years, many MPPT techniques have been advocated, developed and implemented. These methods vary in several aspects such as complexity, required number of sensors, convergence speed, cost, range of effectiveness, ease of hardware implementation etc. Although different methods have been developed by different research groups, very little literature is available, where different MPPT techniques/methods are compared in terms of energy capture, conversion efficiency, response time and reliability. This paper compares the performance of different MPPT methods that are currently used in a solar PV system and also advocates a new MPPT technique which offers better performance than the existing ones. The methodology adopted for analysis is as follows: Initially, a MATLAB based solar PV array model is first developed and validated; then, different MPPT techniques are employed on this PV array under varying temperature and insolation conditions to study the effectiveness of the particular MPPT technique under consideration.

Suggested Citation

  • Mohanty, Parimita & Bhuvaneswari, G. & Balasubramanian, R. & Dhaliwal, Navdeep Kaur, 2014. "MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 581-593.
  • Handle: RePEc:eee:rensus:v:38:y:2014:i:c:p:581-593
    DOI: 10.1016/j.rser.2014.06.001
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    Citations

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    Cited by:

    1. Ridha, Hussein Mohammed & Gomes, Chandima & Hizam, Hashim & Ahmadipour, Masoud & Heidari, Ali Asghar & Chen, Huiling, 2021. "Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Jately, Vibhu & Azzopardi, Brian & Joshi, Jyoti & Venkateswaran V, Balaji & Sharma, Abhinav & Arora, Sudha, 2021. "Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    3. Muhammad Jamshed Abbass & Robert Lis & Faisal Saleem, 2023. "The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm," Energies, MDPI, vol. 16(5), pages 1-13, March.
    4. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    5. Julio López Seguel & Seleme I. Seleme & Lenin M. F. Morais, 2022. "Comparative Study of Buck-Boost, SEPIC, Cuk and Zeta DC-DC Converters Using Different MPPT Methods for Photovoltaic Applications," Energies, MDPI, vol. 15(21), pages 1-26, October.
    6. Farhat, Maissa & Barambones, Oscar & Sbita, Lassaâd, 2015. "Efficiency optimization of a DSP-based standalone PV system using a stable single input fuzzy logic controller," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 907-920.
    7. Sajid Sarwar & Muhammad Annas Hafeez & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Krzysztof Ejsmont, 2022. "A Horse Herd Optimization Algorithm (HOA)-Based MPPT Technique under Partial and Complex Partial Shading Conditions," Energies, MDPI, vol. 15(5), pages 1-22, March.
    8. Li, Shaowu, 2016. "Linear equivalent models at the maximum power point based on variable weather parameters for photovoltaic cell," Applied Energy, Elsevier, vol. 182(C), pages 94-104.
    9. 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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