IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v134y2020ics1364032120306353.html
   My bibliography  Save this article

Survey of maintenance management for photovoltaic power systems

Author

Listed:
  • Peinado Gonzalo, Alfredo
  • Pliego Marugán, Alberto
  • García Márquez, Fausto Pedro

Abstract

The sustainability of the global energy production systems involves new renewable energies and the improvement of the existing ones. Photovoltaic industry is growing thanks to the development of new technologies that increase the performance of photovoltaic systems. These systems are commonly subject to harsh environmental conditions that decrease their energy production and efficiency. In addition, current photovoltaic technologies are more sophisticated, and the size of photovoltaics solar plants is growing. Under this framework, research on failures and degradation mechanisms, together with the improvement of maintenance management, becomes essential to increase the performance, efficiency, reliability, availability, safety, and profitability of these systems. To assess maintenance needs, this paper presents a double contribution: an exhaustive literature review and updated survey on maintenance of photovoltaic plants, and a novel analysis of the current state and a discussion of the future trends and challenges in this field. An analysis of the main faults and degradation mechanisms is done, including the causes, effects, and the main techniques to detect, prevent and mitigate them.

Suggested Citation

  • Peinado Gonzalo, Alfredo & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2020. "Survey of maintenance management for photovoltaic power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:rensus:v:134:y:2020:i:c:s1364032120306353
    DOI: 10.1016/j.rser.2020.110347
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032120306353
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2020.110347?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fillion, R.M. & Riahi, A.R. & Edrisy, A., 2014. "A review of icing prevention in photovoltaic devices by surface engineering," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 797-809.
    2. Harrou, Fouzi & Sun, Ying & Taghezouit, Bilal & Saidi, Ahmed & Hamlati, Mohamed-Elkarim, 2018. "Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches," Renewable Energy, Elsevier, vol. 116(PA), pages 22-37.
    3. Limmanee, Amornrat & Songtrai, Sasiwimon & Udomdachanut, Nuttakarn & Kaewniyompanit, Songpakit & Sato, Yukinobu & Nakaishi, Masaki & Kittisontirak, Songkiate & Sriprapha, Kobsak & Sakamoto, Yukitaka, 2017. "Degradation analysis of photovoltaic modules under tropical climatic conditions and its impacts on LCOE," Renewable Energy, Elsevier, vol. 102(PA), pages 199-204.
    4. Nolden, C. & Barnes, J. & Nicholls, J., 2020. "Community energy business model evolution: A review of solar photovoltaic developments in England," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    5. Huerta Herraiz, Álvaro & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2020. "Photovoltaic plant condition monitoring using thermal images analysis by convolutional neural network-based structure," Renewable Energy, Elsevier, vol. 153(C), pages 334-348.
    6. Ilse, Klemens K. & Figgis, Benjamin W. & Naumann, Volker & Hagendorf, Christian & Bagdahn, Jörg, 2018. "Fundamentals of soiling processes on photovoltaic modules," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 239-254.
    7. Emad Rabiei Hosseinabad & Reinaldo J. Moraga, 2020. "The evaluation of renewable energy predictive modelling in energy dependency reduction: a system dynamics approach," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 12(1), pages 1-22.
    8. Alberto Pliego Marugán & Fausto Pedro García Márquez & Benjamin Lev, 2017. "Optimal decision-making via binary decision diagrams for investments under a risky environment," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5271-5286, September.
    9. Sahoo, Sarat Kumar, 2016. "Renewable and sustainable energy reviews solar photovoltaic energy progress in India: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 927-939.
    10. Saidan, Motasem & Albaali, Abdul Ghani & Alasis, Emil & Kaldellis, John K., 2016. "Experimental study on the effect of dust deposition on solar photovoltaic panels in desert environment," Renewable Energy, Elsevier, vol. 92(C), pages 499-505.
    11. Triki-Lahiani, Asma & Bennani-Ben Abdelghani, Afef & Slama-Belkhodja, Ilhem, 2018. "Fault detection and monitoring systems for photovoltaic installations: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2680-2692.
    12. Zhang, H.L. & Baeyens, J. & Degrève, J. & Cacères, G., 2013. "Concentrated solar power plants: Review and design methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 466-481.
    13. Tsanakas, John A. & Ha, Long & Buerhop, Claudia, 2016. "Faults and infrared thermographic diagnosis in operating c-Si photovoltaic modules: A review of research and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 695-709.
    14. Bouraiou, Ahmed & Hamouda, Messaoud & Chaker, Abdelkader & Lachtar, Salah & Neçaibia, Ammar & Boutasseta, Nadir & Mostefaoui, Mohammed, 2017. "Experimental evaluation of the performance and degradation of single crystalline silicon photovoltaic modules in the Saharan environment," Energy, Elsevier, vol. 132(C), pages 22-30.
    15. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    16. Pawluk, Robert E. & Chen, Yuxiang & She, Yuntong, 2019. "Photovoltaic electricity generation loss due to snow – A literature review on influence factors, estimation, and mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 171-182.
    17. Costa, Suellen C.S. & Diniz, Antonia Sonia A.C. & Kazmerski, Lawrence L., 2018. "Solar energy dust and soiling R&D progress: Literature review update for 2016," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2504-2536.
    18. 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.
    19. Jamil, Wan Juzaili & Abdul Rahman, Hasimah & Shaari, Sulaiman & Salam, Zainal, 2017. "Performance degradation of photovoltaic power system: Review on mitigation methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 876-891.
    20. Chandel, S.S. & Nagaraju Naik, M. & Sharma, Vikrant & Chandel, Rahul, 2015. "Degradation analysis of 28 year field exposed mono-c-Si photovoltaic modules of a direct coupled solar water pumping system in western Himalayan region of India," Renewable Energy, Elsevier, vol. 78(C), pages 193-202.
    21. Maghami, Mohammad Reza & Hizam, Hashim & Gomes, Chandima & Radzi, Mohd Amran & Rezadad, Mohammad Ismael & Hajighorbani, Shahrooz, 2016. "Power loss due to soiling on solar panel: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1307-1316.
    22. Touati, Farid & Al-Hitmi, M.A. & Chowdhury, Noor Alam & Hamad, Jehan Abu & San Pedro Gonzales, Antonio J.R., 2016. "Investigation of solar PV performance under Doha weather using a customized measurement and monitoring system," Renewable Energy, Elsevier, vol. 89(C), pages 564-577.
    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. Li, B. & Delpha, C. & Diallo, D. & Migan-Dubois, A., 2021. "Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    2. Timmidi Nagadurga & Pasumarthi Venkata Ramana Lakshmi Narasimham & V. S. Vakula & Ramesh Devarapalli & Fausto Pedro García Márquez, 2021. "Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm," Energies, MDPI, vol. 14(14), pages 1-23, July.
    3. Segovia Ramírez, Isaac & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2022. "A novel approach to optimize the positioning and measurement parameters in photovoltaic aerial inspections," Renewable Energy, Elsevier, vol. 187(C), pages 371-389.
    4. Thitiphat Klinsuwan & Wachiraphong Ratiphaphongthon & Rabian Wangkeeree & Rattanaporn Wangkeeree & Chatchai Sirisamphanwong, 2023. "Evaluation of Machine Learning Algorithms for Supervised Anomaly Detection and Comparison between Static and Dynamic Thresholds in Photovoltaic Systems," Energies, MDPI, vol. 16(4), pages 1-22, February.
    5. Jamroen, Chaowanan & Fongkerd, Chanon & Krongpha, Wipa & Komkum, Preecha & Pirayawaraporn, Alongkorn & Chindakham, Nachaya, 2021. "A novel UV sensor-based dual-axis solar tracking system: Implementation and performance analysis," Applied Energy, Elsevier, vol. 299(C).
    6. Masoud Emamian & Aref Eskandari & Mohammadreza Aghaei & Amir Nedaei & Amirmohammad Moradi Sizkouhi & Jafar Milimonfared, 2022. "Cloud Computing and IoT Based Intelligent Monitoring System for Photovoltaic Plants Using Machine Learning Techniques," Energies, MDPI, vol. 15(9), pages 1-25, April.
    7. Tang, Wuqin & Yang, Qiang & Dai, Zhou & Yan, Wenjun, 2024. "Module defect detection and diagnosis for intelligent maintenance of solar photovoltaic plants: Techniques, systems and perspectives," Energy, Elsevier, vol. 297(C).
    8. Liu, Lujie & Xiao, Yiyong & Yang, Jun, 2024. "Daily optimization of maintenance routing and scheduling in a large-scale photovoltaic power plant with time-varying output power," Applied Energy, Elsevier, vol. 360(C).
    9. D'Agostino, D. & Minelli, F. & D'Urso, M. & Minichiello, F., 2022. "Fixed and tracking PV systems for Net Zero Energy Buildings: Comparison between yearly and monthly energy balance," Renewable Energy, Elsevier, vol. 195(C), pages 809-824.
    10. Fausto Pedro García Márquez, 2022. "Maintenance Management in Solar Energy Systems," Energies, MDPI, vol. 15(10), pages 1-3, May.
    11. Gabriella-Stefánia Szabó & Róbert Szabó & Loránd Szabó, 2022. "A Review of the Mitigating Methods against the Energy Conversion Decrease in Solar Panels," Energies, MDPI, vol. 15(18), pages 1-21, September.
    12. Weiguo He & Deyang Yin & Kaifeng Zhang & Xiangwen Zhang & Jianyong Zheng, 2021. "Fault Detection and Diagnosis Method of Distributed Photovoltaic Array Based on Fine-Tuning Naive Bayesian Model," Energies, MDPI, vol. 14(14), pages 1-17, July.
    13. Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2024. "Photovoltaic systems operation and maintenance: A review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
    14. 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.

    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. Waqar Akram, M. & Li, Guiqiang & Jin, Yi & Chen, Xiao, 2022. "Failures of Photovoltaic modules and their Detection: A Review," Applied Energy, Elsevier, vol. 313(C).
    2. Conceição, Ricardo & González-Aguilar, José & Merrouni, Ahmed Alami & Romero, Manuel, 2022. "Soiling effect in solar energy conversion systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    3. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    4. Santhakumari, Manju & Sagar, Netramani, 2019. "A review of the environmental factors degrading the performance of silicon wafer-based photovoltaic modules: Failure detection methods and essential mitigation techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 83-100.
    5. 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.
    6. Song, Zhe & Liu, Jia & Yang, Hongxing, 2021. "Air pollution and soiling implications for solar photovoltaic power generation: A comprehensive review," Applied Energy, Elsevier, vol. 298(C).
    7. Costa, Suellen C.S. & Diniz, Antonia Sonia A.C. & Kazmerski, Lawrence L., 2018. "Solar energy dust and soiling R&D progress: Literature review update for 2016," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2504-2536.
    8. Karim Menoufi, 2017. "Dust Accumulation on the Surface of Photovoltaic Panels: Introducing the Photovoltaic Soiling Index (PVSI)," Sustainability, MDPI, vol. 9(6), pages 1-12, June.
    9. Fernández-Solas, Álvaro & Micheli, Leonardo & Almonacid, Florencia & Fernández, Eduardo F., 2021. "Optical degradation impact on the spectral performance of photovoltaic technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    10. Adak, Deepanjana & Bhattacharyya, Raghunath & Barshilia, Harish C., 2022. "A state-of-the-art review on the multifunctional self-cleaning nanostructured coatings for PV panels, CSP mirrors and related solar devices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    11. Chanchangi, Yusuf N. & Ghosh, Aritra & Sundaram, Senthilarasu & Mallick, Tapas K., 2020. "Dust and PV Performance in Nigeria: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    12. Segovia Ramírez, Isaac & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2022. "A novel approach to optimize the positioning and measurement parameters in photovoltaic aerial inspections," Renewable Energy, Elsevier, vol. 187(C), pages 371-389.
    13. Li, B. & Delpha, C. & Diallo, D. & Migan-Dubois, A., 2021. "Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    14. Ganesan, K. & Winston, D. Prince & Nesamalar, J. Jeslin Drusila & Pravin, M., 2024. "Output power enhancement of a bifacial solar photovoltaic with upside down installation during module defects," Applied Energy, Elsevier, vol. 353(PA).
    15. Kim, Byungil & Kim, Changyoon, 2018. "Estimating the effect of module failures on the gross generation of a photovoltaic system using agent-based modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1019-1024.
    16. Huang, Wenfeng & Zhou, Kun & Sun, Ke & He, Zhu, 2019. "Effects of wind flow structure, particle flow and deposition pattern on photovoltaic energy harvest around a block," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Alshawaf, Mohammad & Poudineh, Rahmatallah & Alhajeri, Nawaf S., 2020. "Solar PV in Kuwait: The effect of ambient temperature and sandstorms on output variability and uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    18. Høiaas, Ingeborg & Grujic, Katarina & Imenes, Anne Gerd & Burud, Ingunn & Olsen, Espen & Belbachir, Nabil, 2022. "Inspection and condition monitoring of large-scale photovoltaic power plants: A review of imaging technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    19. Bouraiou, Ahmed & Hamouda, Messaoud & Chaker, Abdelkader & Lachtar, Salah & Neçaibia, Ammar & Boutasseta, Nadir & Mostefaoui, Mohammed, 2017. "Experimental evaluation of the performance and degradation of single crystalline silicon photovoltaic modules in the Saharan environment," Energy, Elsevier, vol. 132(C), pages 22-30.
    20. Singh, Rashmi & Sharma, Madhu & Rawat, Rahul & Banerjee, Chandan, 2018. "An assessment of series resistance estimation techniques for different silicon based SPV modules," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 199-216.

    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:eee:rensus:v:134:y:2020:i:c:s1364032120306353. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.