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An accurate analytical modeling of solar photovoltaic system considering Rs and Rsh under partial shaded condition

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  • Sampath Kumar Vankadara

    (Lovely Professional University
    Bharat Institute of Engineering and Technology)

  • Shamik Chatterjee

    (Lovely Professional University)

  • Praveen Kumar Balachandran

    (Vardhaman College of Engineering)

Abstract

Photovoltaic (PV) systems are subjected to several environmental disturbances, one such a disturbance is partial shading, which adversely alters the characteristics of the photovoltaic system. Therefore, under Partial Shading Condition (PSC) there is a need to develop a complete analytical model of the PV system to investigate the most appropriate maximum power point tracking (MPPT) strategy in larger PV Systems. Based on the necessity, a precise analytical model of the PV system under PSC considering the effect of both series and shunt resistance is developed. The effects of temperature changes, irradiation changes, and effect for change in series, and shunt resistance and PSCs on electrical characteristics of the PV array are examined. A comparison was made with real-time data over the proposed and existing models during various PSCs. The results proved that the reliability of the proposed model is good, and it can be used to model different ranges of photovoltaic systems for both standalone and grid-integrated systems.

Suggested Citation

  • Sampath Kumar Vankadara & Shamik Chatterjee & Praveen Kumar Balachandran, 2022. "An accurate analytical modeling of solar photovoltaic system considering Rs and Rsh under partial shaded condition," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2472-2481, October.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:5:d:10.1007_s13198-022-01658-6
    DOI: 10.1007/s13198-022-01658-6
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    References listed on IDEAS

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    Cited by:

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    3. Hossam Hassan Ali & Mohamed Ebeed & Ahmed Fathy & Francisco Jurado & Thanikanti Sudhakar Babu & Alaa A. Mahmoud, 2023. "A New Hybrid Multi-Population GTO-BWO Approach for Parameter Estimation of Photovoltaic Cells and Modules," Sustainability, MDPI, vol. 15(14), pages 1-33, July.
    4. Jingwei Zhang & Zenan Yang & Kun Ding & Li Feng & Frank Hamelmann & Xihui Chen & Yongjie Liu & Ling Chen, 2022. "Modeling of Photovoltaic Array Based on Multi-Agent Deep Reinforcement Learning Using Residuals of I–V Characteristics," Energies, MDPI, vol. 15(18), pages 1-17, September.

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