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A maximum power point tracking for photovoltaic systems based on Monod equation

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  • Camilo, Jones C.
  • Guedes, Tatiana
  • Fernandes, Darlan A.
  • Melo, J.D.
  • Costa, F.F.
  • Sguarezi Filho, Alfeu J.

Abstract

This paper presents a maximum power point tracking (MPPT) algorithm based on the Monod equation for photovoltaic (PV) systems with DC regulation. This equation is applied to estimate the power output for each current output of PV generator. The proposed MPPT permits to quickly estimate the required duty-cycle by the step-up converter that is associated with the provided maximum power from the generator. The new MPPT algorithm has a lower implementation complexity and with a lower computational effort, which is important to implement using less expensive controllers and low cost processor. The proposed algorithm is tested in a PV system composed by solar module that emulates of PV generator and which the input voltage is regulated by a push-pull converter, supplying a DC load. The experimental results demonstrate that use of the Monod equation improves the dynamics of the PV system and find the maximum value of power for conditions of low irradiance unlike other methodologies.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:130:y:2019:i:c:p:428-438
    DOI: 10.1016/j.renene.2018.06.017
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    1. Liu, Liqun & Meng, Xiaoli & Liu, Chunxia, 2016. "A review of maximum power point tracking methods of PV power system at uniform and partial shading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1500-1507.
    2. Bradai, R. & Boukenoui, R. & Kheldoun, A. & Salhi, H. & Ghanes, M. & Barbot, J-P. & Mellit, A., 2017. "Experimental assessment of new fast MPPT algorithm for PV systems under non-uniform irradiance conditions," Applied Energy, Elsevier, vol. 199(C), pages 416-429.
    3. Sundareswaran, K. & Vignesh kumar, V. & Palani, S., 2015. "Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions," Renewable Energy, Elsevier, vol. 75(C), pages 308-317.
    4. Mohapatra, Alivarani & Nayak, Byamakesh & Das, Priti & Mohanty, Kanungo Barada, 2017. "A review on MPPT techniques of PV system under partial shading condition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 854-867.
    5. Ahmed, Jubaer & Salam, Zainal, 2015. "An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency," Applied Energy, Elsevier, vol. 150(C), pages 97-108.
    6. 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.
    7. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
    8. Kofinas, P. & Doltsinis, S. & Dounis, A.I. & Vouros, G.A., 2017. "A reinforcement learning approach for MPPT control method of photovoltaic sources," Renewable Energy, Elsevier, vol. 108(C), pages 461-473.
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    Cited by:

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    2. Astitva Kumar & Mohammad Rizwan & Uma Nangia & Muhannad Alaraj, 2021. "Grey Wolf Optimizer-Based Array Reconfiguration to Enhance Power Production from Solar Photovoltaic Plants under Different Scenarios," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    3. Shaowu Li & Kunyi Chen & Qin Li & Qing Ai, 2022. "A Variable-Weather-Parameter MPPT Method Based on Equation Solution for Photovoltaic System with DC Bus," Energies, MDPI, vol. 15(18), pages 1-25, September.
    4. 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).
    5. 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.

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