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A Time-Series Data Analysis Methodology for Effective Monitoring of Partially Shaded Photovoltaic Systems

Author

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  • Odysseas Tsafarakis

    (Copernicus institute of Sustainable Development, Utrecht University, 3564 CB Utrecht, The Netherlands)

  • Kostas Sinapis

    (Solar Energy Application Centre, 5656 AE Eindhoven, The Netherlands)

  • Wilfried G. J. H. M. van Sark

    (Copernicus institute of Sustainable Development, Utrecht University, 3564 CB Utrecht, The Netherlands)

Abstract

The majority of photovoltaic (PV) systems in the Netherlands are small scale, and installed on residential and commercial rooftops, where different objects in many cases may lead to the presence of shading and inevitable energy loss. Nevertheless, the energy loss due to expected shadow must be distinguished from the energy loss due to other malfunctions. In this study an algorithmic tool is presented that automates the process of analyzing monitoring data of partially shaded PV systems. The algorithm compares long-term and high-resolution yield data of a partially shaded PV system with the yield data of an unshaded PV system, as reference PV system, and automatically detects the energy loss due to the expected shadow, caused by any surrounding obstacles, and distinguishes it from any additional energy loss due to other malfunctions. This study focuses on PV systems with module-level power electronics (MLPE) since these are mostly used on PV systems on rooftops. Three different cases of shaded MLPE PV systems are presented to illustrate the versatility of the methodology. Furthermore, suggestions for further research are discussed at the end of the paper.

Suggested Citation

  • Odysseas Tsafarakis & Kostas Sinapis & Wilfried G. J. H. M. van Sark, 2019. "A Time-Series Data Analysis Methodology for Effective Monitoring of Partially Shaded Photovoltaic Systems," Energies, MDPI, vol. 12(9), pages 1-18, May.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1722-:d:228922
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    References listed on IDEAS

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    1. Eke, Rustu & Senturk, Ali, 2013. "Monitoring the performance of single and triple junction amorphous silicon modules in two building integrated photovoltaic (BIPV) installations," Applied Energy, Elsevier, vol. 109(C), pages 154-162.
    2. Odysseas Tsafarakis & Kostas Sinapis & Wilfried G. J. H. M. Van Sark, 2018. "PV System Performance Evaluation by Clustering Production Data to Normal and Non-Normal Operation," Energies, MDPI, vol. 11(4), pages 1-19, April.
    3. Martin Libra & Milan Daneček & Jan Lešetický & Vladislav Poulek & Jan Sedláček & Václav Beránek, 2019. "Monitoring of Defects of a Photovoltaic Power Plant Using a Drone," Energies, MDPI, vol. 12(5), pages 1-9, February.
    4. Panagiotis Moraitis & Bala Bhavya Kausika & Nick Nortier & Wilfried Van Sark, 2018. "Urban Environment and Solar PV Performance: The Case of the Netherlands," Energies, MDPI, vol. 11(6), pages 1-14, May.
    5. Chine, W. & Mellit, A. & Pavan, A. Massi & Kalogirou, S.A., 2014. "Fault detection method for grid-connected photovoltaic plants," Renewable Energy, Elsevier, vol. 66(C), pages 99-110.
    6. Bressan, M. & El Basri, Y. & Galeano, A.G. & Alonso, C., 2016. "A shadow fault detection method based on the standard error analysis of I-V curves," Renewable Energy, Elsevier, vol. 99(C), pages 1181-1190.
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    Cited by:

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    2. Ewa Klugmann-Radziemska, 2020. "Shading, Dusting and Incorrect Positioning of Photovoltaic Modules as Important Factors in Performance Reduction," Energies, MDPI, vol. 13(8), pages 1-12, April.
    3. Vytautas Bocullo & Linas Martišauskas & Darius Pupeikis & Ramūnas Gatautis & Rytis Venčaitis & Rimantas Bakas, 2023. "UAV Photogrammetry Application for Determining the Influence of Shading on Solar Photovoltaic Array Energy Efficiency," Energies, MDPI, vol. 16(3), pages 1-19, January.
    4. Ngoc Thien Le & Thanh Le Truong & Widhyakorn Asdornwised & Surachai Chaitusaney & Watit Benjapolakul, 2023. "Energy Production Analysis of Rooftop PV Systems Equipped with Module-Level Power Electronics under Partial Shading Conditions Based on Mixed-Effects Model," Energies, MDPI, vol. 16(2), pages 1-15, January.

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