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Prognostic Methods for Photovoltaic Systems’ Underperformance and Degradation: Status, Perspectives, and Challenges

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  • Gianfranco Di Lorenzo

    (Department of Astronautical, Electrical and Energy Engineering Sapienza, University of Rome, Via Eudossiana 18, 00184 Rome, Italy)

  • Erika Stracqualursi

    (Department of Astronautical, Electrical and Energy Engineering Sapienza, University of Rome, Via Eudossiana 18, 00184 Rome, Italy)

  • Leonardo Micheli

    (Department of Astronautical, Electrical and Energy Engineering Sapienza, University of Rome, Via Eudossiana 18, 00184 Rome, Italy)

  • Salvatore Celozzi

    (Department of Astronautical, Electrical and Energy Engineering Sapienza, University of Rome, Via Eudossiana 18, 00184 Rome, Italy)

  • Rodolfo Araneo

    (Department of Astronautical, Electrical and Energy Engineering Sapienza, University of Rome, Via Eudossiana 18, 00184 Rome, Italy)

Abstract

The ongoing energy crisis and the rising prices of fossil fuels have accelerated the need for a renewable energy transition [...]

Suggested Citation

  • Gianfranco Di Lorenzo & Erika Stracqualursi & Leonardo Micheli & Salvatore Celozzi & Rodolfo Araneo, 2022. "Prognostic Methods for Photovoltaic Systems’ Underperformance and Degradation: Status, Perspectives, and Challenges," Energies, MDPI, vol. 15(17), pages 1-6, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6413-:d:904772
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    References listed on IDEAS

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    1. Silvano Vergura, 2020. "Bollinger Bands Based on Exponential Moving Average for Statistical Monitoring of Multi-Array Photovoltaic Systems," Energies, MDPI, vol. 13(15), pages 1-14, August.
    2. Sascha Lindig & Atse Louwen & David Moser & Marko Topic, 2020. "Outdoor PV System Monitoring—Input Data Quality, Data Imputation and Filtering Approaches," Energies, MDPI, vol. 13(19), pages 1-18, September.
    3. Fabiana Lisco & Farwah Bukhari & Soňa Uličná & Kenan Isbilir & Kurt L. Barth & Alan Taylor & John M. Walls, 2020. "Degradation of Hydrophobic, Anti-Soiling Coatings for Solar Module Cover Glass," Energies, MDPI, vol. 13(15), pages 1-15, July.
    4. Mario Tovar & Miguel Robles & Felipe Rashid, 2020. "PV Power Prediction, Using CNN-LSTM Hybrid Neural Network Model. Case of Study: Temixco-Morelos, México," Energies, MDPI, vol. 13(24), pages 1-15, December.
    5. Antonia Sônia A. C. Diniz & Tulio P. Duarte & Suellen A. C. Costa & Daniel Sena Braga & Vinicius Camatta Santana & Lawrence L. Kazmerski, 2022. "Soiling Spectral and Module Temperature Effects: Comparisons of Competing Operating Parameters for Four Commercial PV Module Technologies," Energies, MDPI, vol. 15(15), pages 1-18, July.
    6. Lisa B. Bosman & Walter D. Leon-Salas & William Hutzel & Esteban A. Soto, 2020. "PV System Predictive Maintenance: Challenges, Current Approaches, and Opportunities," Energies, MDPI, vol. 13(6), pages 1-16, March.
    7. Silvano Vergura, 2022. "Criticalities of the Outdoor Infrared Inspection of Photovoltaic Modules by Means of Drones," Energies, MDPI, vol. 15(14), pages 1-19, July.
    8. Antonello Rosato & Rosa Altilio & Rodolfo Araneo & Massimo Panella, 2017. "Prediction in Photovoltaic Power by Neural Networks," Energies, MDPI, vol. 10(7), pages 1-25, July.
    9. Michael W. Hopwood & Lekha Patel & Thushara Gunda, 2022. "Classification of Photovoltaic Failures with Hidden Markov Modeling, an Unsupervised Statistical Approach," Energies, MDPI, vol. 15(14), pages 1-12, July.
    10. Julián Ascencio-Vásquez & Ismail Kaaya & Kristijan Brecl & Karl-Anders Weiss & Marko Topič, 2019. "Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules," Energies, MDPI, vol. 12(24), pages 1-16, December.
    11. Emilio Ghiani & Andrea Giordano & Andrea Nieddu & Luca Rosetti & Fabrizio Pilo, 2019. "Planning of a Smart Local Energy Community: The Case of Berchidda Municipality (Italy)," Energies, MDPI, vol. 12(24), pages 1-14, December.
    12. Spyros Theocharides & Marios Theristis & George Makrides & Marios Kynigos & Chrysovalantis Spanias & George E. Georghiou, 2021. "Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting," Energies, MDPI, vol. 14(4), pages 1-22, February.
    13. Roberto Pierdicca & Marina Paolanti & Andrea Felicetti & Fabio Piccinini & Primo Zingaretti, 2020. "Automatic Faults Detection of Photovoltaic Farms: solAIr, a Deep Learning-Based System for Thermal Images," Energies, MDPI, vol. 13(24), pages 1-17, December.
    14. Nailya Maitanova & Jan-Simon Telle & Benedikt Hanke & Matthias Grottke & Thomas Schmidt & Karsten von Maydell & Carsten Agert, 2020. "A Machine Learning Approach to Low-Cost Photovoltaic Power Prediction Based on Publicly Available Weather Reports," Energies, MDPI, vol. 13(3), pages 1-23, February.
    15. Hamid Iftikhar & Eduardo Sarquis & P. J. Costa Branco, 2021. "Why Can Simple Operation and Maintenance (O&M) Practices in Large-Scale Grid-Connected PV Power Plants Play a Key Role in Improving Its Energy Output?," Energies, MDPI, vol. 14(13), pages 1-29, June.
    16. Dong Ho Lee & Jong Hwa Park, 2019. "Developing Inspection Methodology of Solar Energy Plants by Thermal Infrared Sensor on Board Unmanned Aerial Vehicles," Energies, MDPI, vol. 12(15), pages 1-14, July.
    17. Thiago A. Felipe & Fernando C. Melo & Luiz C. G. Freitas, 2021. "Design and Development of an Online Smart Monitoring and Diagnosis System for Photovoltaic Distributed Generation," Energies, MDPI, vol. 14(24), pages 1-13, December.
    18. Jaeun Kim & Matheus Rabelo & Siva Parvathi Padi & Hasnain Yousuf & Eun-Chel Cho & Junsin Yi, 2021. "A Review of the Degradation of Photovoltaic Modules for Life Expectancy," Energies, MDPI, vol. 14(14), pages 1-21, July.
    19. Gabriele Roggi & Alessandro Niccolai & Francesco Grimaccia & Marco Lovera, 2020. "A Computer Vision Line-Tracking Algorithm for Automatic UAV Photovoltaic Plants Monitoring Applications," Energies, MDPI, vol. 13(4), pages 1-15, February.
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