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Number of maximum power points in photovoltaic arrays during partial shading events by clouds

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  • Lappalainen, Kari
  • Valkealahti, Seppo

Abstract

This article presents a study of the number of maximum power points (MPPs) of photovoltaic (PV) module arrays during partial shading events by clouds. Around 9000 shadow edges were identified in measured irradiance data, and the electrical characteristics of 250–500 PV module arrays with different configurations were studied during the irradiance changes. It was found that most of the partial shading events caused by clouds do not cause multiple MPPs for PV arrays, even for a moment. The number of MPPs was found to decrease with the increasing number of parallel-connected PV strings, but to increase strongly with the increasing length of the strings. According to the results, the use of a total-cross-tied electrical PV array configuration leads to worse system performance compared to a simple series-parallel configuration during partial shading events. Dark shadows with sharp edges moving parallel to the PV strings caused the largest MPP numbers, up to 20. The results show that energy losses due to operation at a local MPP instead of the global one during partial shading events by clouds have only a minor effect on the total energy production of PV arrays.

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  • Lappalainen, Kari & Valkealahti, Seppo, 2020. "Number of maximum power points in photovoltaic arrays during partial shading events by clouds," Renewable Energy, Elsevier, vol. 152(C), pages 812-822.
    • Handle: RePEc:eee:renene:v:152:y:2020:i:c:p:812-822
    DOI: 10.1016/j.renene.2020.01.119
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    References listed on IDEAS

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    1. Satpathy, Priya Ranjan & Jena, Sasmita & Sharma, Renu, 2018. "Power enhancement from partially shaded modules of solar PV arrays through various interconnections among modules," Energy, Elsevier, vol. 144(C), pages 839-850.
    2. 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.
    3. Lappalainen, Kari & Valkealahti, Seppo, 2017. "Output power variation of different PV array configurations during irradiance transitions caused by moving clouds," Applied Energy, Elsevier, vol. 190(C), pages 902-910.
    4. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
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    Cited by:

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    2. Arturo Y. Jaen-Cuellar & David A. Elvira-Ortiz & Roque A. Osornio-Rios & Jose A. Antonino-Daviu, 2022. "Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review," Energies, MDPI, vol. 15(15), pages 1-36, July.
    3. Yin, Rumeng & He, Jiang, 2023. "Design of a photovoltaic electric bike battery-sharing system in public transit stations," Applied Energy, Elsevier, vol. 332(C).
    4. Moreira, Hugo Soeiro & Lucas de Souza Silva, João & Gomes dos Reis, Marcos Vinicios & de Bastos Mesquita, Daniel & Kikumoto de Paula, Bruno Henrique & Villalva, Marcelo Gradella, 2021. "Experimental comparative study of photovoltaic models for uniform and partially shading conditions," Renewable Energy, Elsevier, vol. 164(C), pages 58-73.
    5. Chepp, Ellen David & Gasparin, Fabiano Perin & Krenzinger, Arno, 2022. "Improvements in methods for analysis of partially shaded PV modules," Renewable Energy, Elsevier, vol. 200(C), pages 900-910.
    6. Mirza, Adeel Feroz & Mansoor, Majad & Zhan, Keyu & Ling, Qiang, 2021. "High-efficiency swarm intelligent maximum power point tracking control techniques for varying temperature and irradiance," Energy, Elsevier, vol. 228(C).

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