IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i9p1722-d228922.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/9/1722/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/9/1722/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luis Miguel Pérez Archila & Juan David Bastidas-Rodríguez & Rodrigo Correa & Luz Adriana Trejos Grisales & Daniel Gonzalez-Montoya, 2020. "A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms," Energies, MDPI, vol. 13(4), pages 1-22, February.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    2. Pillai, Dhanup S. & Rajasekar, N., 2018. "A comprehensive review on protection challenges and fault diagnosis in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 18-40.
    3. Livera, Andreas & Theristis, Marios & Makrides, George & Georghiou, George E., 2019. "Recent advances in failure diagnosis techniques based on performance data analysis for grid-connected photovoltaic systems," Renewable Energy, Elsevier, vol. 133(C), pages 126-143.
    4. Wilfried van Sark, 2019. "Photovoltaic System Design and Performance," Energies, MDPI, vol. 12(10), pages 1-6, May.
    5. Qamar Navid & Ahmed Hassan & Abbas Ahmad Fardoun & Rashad Ramzan & Abdulrahman Alraeesi, 2021. "Fault Diagnostic Methodologies for Utility-Scale Photovoltaic Power Plants: A State of the Art Review," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    6. Bressan, M. & Gutierrez, A. & Garcia Gutierrez, L. & Alonso, C., 2018. "Development of a real-time hot-spot prevention using an emulator of partially shaded PV systems," Renewable Energy, Elsevier, vol. 127(C), pages 334-343.
    7. Sahoo, Somadutta & Zuidema, Christian & van Stralen, Joost N.P. & Sijm, Jos & Faaij, André, 2022. "Detailed spatial analysis of renewables’ potential and heat: A study of Groningen Province in the northern Netherlands," Applied Energy, Elsevier, vol. 318(C).
    8. Mahmoud Dhimish & Pavlos I. Lazaridis, 2022. "Approximating Shading Ratio Using the Total-Sky Imaging System: An Application for Photovoltaic Systems," Energies, MDPI, vol. 15(21), pages 1-16, November.
    9. Kara Mostefa Khelil, Chérifa & Amrouche, Badia & Benyoucef, Abou soufiane & Kara, Kamel & Chouder, Aissa, 2020. "New Intelligent Fault Diagnosis (IFD) approach for grid-connected photovoltaic systems," Energy, Elsevier, vol. 211(C).
    10. Chikh, Madjid & Berkane, Smain & Mahrane, Achour & Sellami, Rabah & Yassaa, Noureddine, 2021. "Performance assessment of a 400 kWp multi- technology photovoltaic grid-connected pilot plant in arid region of Algeria," Renewable Energy, Elsevier, vol. 172(C), pages 488-501.
    11. Thiago B. Murari & Aloisio S. Nascimento Filho & Marcelo A. Moret & Sergio Pitombo & Alex A. B. Santos, 2020. "Self-Affine Analysis of ENSO in Solar Radiation," Energies, MDPI, vol. 13(18), pages 1-17, September.
    12. Antonio Barragán-Escandón & Esteban Zalamea-León & Julio Terrados-Cepeda, 2019. "Incidence of Photovoltaics in Cities Based on Indicators of Occupancy and Urban Sustainability," Energies, MDPI, vol. 12(5), pages 1-26, February.
    13. Cannavale, Alessandro & Ierardi, Laura & Hörantner, Maximilian & Eperon, Giles E. & Snaith, Henry J. & Ayr, Ubaldo & Martellotta, Francesco, 2017. "Improving energy and visual performance in offices using building integrated perovskite-based solar cells: A case study in Southern Italy," Applied Energy, Elsevier, vol. 205(C), pages 834-846.
    14. Dhimish, Mahmoud & Holmes, Violeta & Dales, Mark, 2017. "Parallel fault detection algorithm for grid-connected photovoltaic plants," Renewable Energy, Elsevier, vol. 113(C), pages 94-111.
    15. Carlos Toledo & Lucía Serrano-Lujan & Jose Abad & Antonio Lampitelli & Antonio Urbina, 2019. "Measurement of Thermal and Electrical Parameters in Photovoltaic Systems for Predictive and Cross-Correlated Monitorization," Energies, MDPI, vol. 12(4), pages 1-20, February.
    16. Alessandro Cannavale & Francesco Martellotta & Francesco Fiorito & Ubaldo Ayr, 2020. "The Challenge for Building Integration of Highly Transparent Photovoltaics and Photoelectrochromic Devices," Energies, MDPI, vol. 13(8), pages 1-24, April.
    17. Pavel Kuznetsov & Dmitry Kotelnikov & Leonid Yuferev & Vladimir Panchenko & Vadim Bolshev & Marek Jasiński & Aymen Flah, 2022. "Method for the Automated Inspection of the Surfaces of Photovoltaic Modules," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    18. Mariusz T. Sarniak, 2020. "Researches of the Impact of the Nominal Power Ratio and Environmental Conditions on the Efficiency of the Photovoltaic System: A Case Study for Poland in Central Europe," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    19. Ren, Xiao & Li, Jing & Hu, Mingke & Pei, Gang & Jiao, Dongsheng & Zhao, Xudong & Ji, Jie, 2019. "Feasibility of an innovative amorphous silicon photovoltaic/thermal system for medium temperature applications," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    20. Mellit, A. & Tina, G.M. & Kalogirou, S.A., 2018. "Fault detection and diagnosis methods for photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1-17.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1722-:d:228922. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.