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Investigation of the Partial Shading Effect of Photovoltaic Panels and Optimization of Their Performance Based on High-Efficiency FLC Algorithm

Author

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  • Dan Craciunescu

    (Department of Mechanical Engineering, Faculty of Mechanical Engineering and Mechatronics, Polytechnic University of Bucharest, Independence Street no. 13, District 6, 060042 Bucharest, Romania)

  • Laurentiu Fara

    (Department of Applied Physics, Faculty of Applied Sciences, Polytechnic University of Bucharest, Independence Street no. 13, District 6, 060042 Bucharest, Romania
    Academy of Romanian Scientists (AOSR), Ilfov Street 3, 030167 Bucharest, Romania)

Abstract

The present work proposes an enhanced method of investigation and optimization photovoltaic (PV) modules by approaching and using MPPT (Maximum Power Point Tracking) technique to improve their output power. The performance of the PV panels is strongly influenced by the operating conditions, especially regarding the solar irradiance, temperature, configuration, and the shading (due to a passing cloud or neighboring buildings); all these cause, both on energy conversion loss, and further on non-linearity of the I-V characteristics. From this reason, the present study could have a high relevance based on the improvement of the performances (including the efficiency) of the shaded photovoltaic panels and would quantify the impact of a complex approach represented by numerical modeling and experimental validation. For a better understanding of these issues determined by partial shading, and improvement of MPP tracking, it is required to study the behavior of individual panels. For the best accuracy of the implemented models a comparative analysis and optimized method of the PV modules was considered based on: (1) the influence of temperature and solar irradiance and behavior of the PV modules in partial shading conditions; (2) a comparison between the optimized output power of four algorithms (FLC—Fuzzy Logic Controller, P&O—Perturb and Observe, IncCond—Incremental Conductance and RC Ripple Correlation) and the selection of the best one (FLC); (3) discussion of customized/improved fuzzy logic controller (FLC) algorithm on five operation points introduced in order to increase PV module efficiency under fluctuating weather conditions and rapidly changing uncertainties. Furthermore, the FLC provides a set of rules useful for predicting the current-voltage behavior and the maximum power points of shaded photovoltaic modules. This FLC algorithm was implemented in a specialized software, namely MATLAB/Simulink. The authors highlighted the development and implementation of a numerical simulation model for an advanced PV module to determine its behavior under different operating conditions and improve its performance. The essence of the authors’ research and the motivation of this work is described. The authors were able to stabilize and improve the output performance of the PV module. The results concerning the shading effect as well as the shading patterns were developed, demonstrated, and experimentally validated. These results could be applied for the actual photovoltaic installations, respectively complex stand-alone or grid-connected photovoltaic systems.

Suggested Citation

  • Dan Craciunescu & Laurentiu Fara, 2023. "Investigation of the Partial Shading Effect of Photovoltaic Panels and Optimization of Their Performance Based on High-Efficiency FLC Algorithm," Energies, MDPI, vol. 16(3), pages 1-28, January.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1169-:d:1042817
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    References listed on IDEAS

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    1. Sameti, Mohammad & Haghighat, Fariborz, 2018. "Integration of distributed energy storage into net-zero energy district systems: Optimum design and operation," Energy, Elsevier, vol. 153(C), pages 575-591.
    2. Laurentiu Fara & Dan Craciunescu & Silvian Fara, 2021. "Numerical Modelling and Digitalization Analysis for a Photovoltaic Pumping System Placed in the South of Romania," Energies, MDPI, vol. 14(10), pages 1-21, May.
    3. Bozorgavari, Seyed Aboozar & Aghaei, Jamshid & Pirouzi, Sasan & Nikoobakht, Ahmad & Farahmand, Hossein & Korpås, Magnus, 2020. "Robust planning of distributed battery energy storage systems in flexible smart distribution networks: A comprehensive study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    4. Huang, Pei & Lovati, Marco & Zhang, Xingxing & Bales, Chris, 2020. "A coordinated control to improve performance for a building cluster with energy storage, electric vehicles, and energy sharing considered," Applied Energy, Elsevier, vol. 268(C).
    5. Syed Zulqadar Hassan & Hui Li & Tariq Kamal & Uğur Arifoğlu & Sidra Mumtaz & Laiq Khan, 2017. "Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems," Energies, MDPI, vol. 10(3), pages 1-16, March.
    6. Divine Atsu & Alok Dhaundiyal, 2019. "Effect of Ambient Parameters on the Temperature Distribution of Photovoltaic (PV) Modules," Resources, MDPI, vol. 8(2), pages 1-12, June.
    7. Alonso Gutiérrez Galeano & Michael Bressan & Fernando Jiménez Vargas & Corinne Alonso, 2018. "Shading Ratio Impact on Photovoltaic Modules and Correlation with Shading Patterns," Energies, MDPI, vol. 11(4), pages 1-26, April.
    8. 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.
    9. Sardi, Junainah & Mithulananthan, N. & Hung, Duong Quoc, 2017. "Strategic allocation of community energy storage in a residential system with rooftop PV units," Applied Energy, Elsevier, vol. 206(C), pages 159-171.
    10. Qiang Zhao & Shuai Shao & Lingxing Lu & Xin Liu & Honglu Zhu, 2018. "A New PV Array Fault Diagnosis Method Using Fuzzy C-Mean Clustering and Fuzzy Membership Algorithm," Energies, MDPI, vol. 11(1), pages 1-21, January.
    11. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2016. "Optimum community energy storage system for demand load shifting," Applied Energy, Elsevier, vol. 174(C), pages 130-143.
    12. Carlos Robles Algarín & John Taborda Giraldo & Omar Rodríguez Álvarez, 2017. "Fuzzy Logic Based MPPT Controller for a PV System," Energies, MDPI, vol. 10(12), pages 1-18, December.
    13. Pei Huang & Xingxing Zhang & Benedetta Copertaro & Puneet Kumar Saini & Da Yan & Yi Wu & Xiangjie Chen, 2020. "A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)," Sustainability, MDPI, vol. 12(17), pages 1-37, August.
    14. Kamran Ali Khan Niazi & Yongheng Yang & Mashood Nasir & Dezso Sera, 2019. "Evaluation of Interconnection Configuration Schemes for PV Modules with Switched-Inductor Converters under Partial Shading Conditions," Energies, MDPI, vol. 12(14), pages 1-12, July.
    15. Varaha Satya Bharath Kurukuru & Frede Blaabjerg & Mohammed Ali Khan & Ahteshamul Haque, 2020. "A Novel Fault Classification Approach for Photovoltaic Systems," Energies, MDPI, vol. 13(2), pages 1-17, January.
    16. Luthander, Rasmus & Widén, Joakim & Munkhammar, Joakim & Lingfors, David, 2016. "Self-consumption enhancement and peak shaving of residential photovoltaics using storage and curtailment," Energy, Elsevier, vol. 112(C), pages 221-231.
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    1. Muhammed Y. Worku & Mohamed A. Hassan & Luqman S. Maraaba & Md Shafiullah & Mohamed R. Elkadeem & Md Ismail Hossain & Mohamed A. Abido, 2023. "A Comprehensive Review of Recent Maximum Power Point Tracking Techniques for Photovoltaic Systems under Partial Shading," Sustainability, MDPI, vol. 15(14), pages 1-28, July.

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