Challenges during commissioning and operation in photovoltaic power plants by electrical faults
Abstract
Problems such as increasing environmental pollution and global warming due to fossil fuels used in energy production have revealed the requirement for renewable energy sources. In addition to this situation, the decreasing fossil fuel reserves, and the need to diversify energy production resources to ensure energy supply security for countries have made the use of renewable energy sources a necessity. Therefore, demand for solar energy will continue to increase, considering the increasing renewable energy need. To increase energy efficiency, the uninterrupted production of photovoltaic power plants during production hours is important to reduce the consumption of fossil fuels. For this reason, situations and malfunctions that prevent uninterrupted operations should be detected. Fault classification contributes to the rapid identification of problems by providing fast diagnostics for possible faults. When the previous studies in this field are examined, there are publications about general faults in photovoltaic power plants and publications about electrical faults separately. However, there are limitations in academic studies that deal with the difficulties encountered in the commissioning and operation of photovoltaic power plants in detail and examine electrical faults. In this context, there is a need for relevant studies. In this study, the possible failures that may occur during the commissioning and operation of photovoltaic power plants will be categorized and this study is intended to be a resource for studies on this subject. It is aimed to create a resource for academic studies and to contribute to field applications to companies in the sector.
Full Text:
PDFReferences
A. E. Lazzaretti, C.H.d. Costa, M.P. Rodrigues, G.D. Yamada, G. Lexinoski, G.L. Moritz, E. Oroski, R.E.d. Goes, R.R. Linhares, P.C. Stadzisz, J.S. Omori, R.B.d. Santos, “A monitoring system for online fault detection and classification in photovoltaic plants,” Sensors, vol. 20, pp. 4688, September 2020.
A. Abubakar, M. A. Carlos Frederico, & M. Gemignani, “Review of artificial intelligence-based failure detection and diagnosis methods for solar photovoltaic systems,” Machines, 9(12), pp. 328, 2021.
F. Öncin, “Connection criteria of roof type solar energy power plants and distribution facilities,” Master’s thesis, Gazi University Institute of Pure and Applied Sciences, Ankara, Türkiye, February 2018.
N, Mansouri, A. Lashab, D. Sera, J. M. Guerrero, A. Cherif, “Large Photovoltaic Power Plants Integration: A Review of Challenges and Solutions,” Energies, vol. 12, pp. 3798, October 2019.
M. Ahmadipour, H. Hizam, M. L. Othman, M.A. Mohd Radzi, N. Chireh, “A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine,” Energies, vol. 12, pp. 2508, June 2019.
E. Rakhshani, K. Rouzbehi, A. J. Sánchez, A.C. Tobar, E. Pouresmaeil, “Integration of Large Scale PV-Based Generation into Power Systems: A Survey,” Energies, 12, 1425, April 2019.
A. Mellit, G.M. Tina, S.A. Kalogirou, “Fault detection and diagnosis methods for photovoltaic systems: A review,” Renewable and Sustainable Energy Reviews, vol. 91, pp. 1-17, April 2018.
M. H. Alsharif, J. Kim, J.H. Kim, “Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review,” Sustainability, vol. 10, pp. 1822, June 2018.
S.R. Madeti, S.N. Singh, “A comprehensive study on different types of faults and detection techniques for solar photovoltaic system,” Solar Energy, vol. 158, October 2017.
M. Dhimish, V. Holmes, M. Dales, “Parallel fault detection algorithm for grid-connected photovoltaic plants,” Renewable Energy, vol. 113, pp. 94-111, May 2017.
M. K. Alam, F. Khan, J. Johnson, and J. Flicker, “A Comprehensive Review of Catastrophic Faults in PV Arrays: Types, Detection, and Mitigation Techniques,” IEEE Journal of Photovoltaics, 5(3), pp. 982-997, 2015.
Zhicong Chen, Lijun Wu, Shuying Cheng, Peijie Lin, Yue Wu, Wencheng Lin, “Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics,” Applied Energy, vol. 204, pp. 912-934, May 2017.
V.S.B. Kurukuru, F. Blaabjerg, M.A. Khan, A. Haque, “A Novel Fault Classification Approach for Photovoltaic Systems,” Energies, vol. 13, pp. 308, January 2020.
T. Berghout, M. Benbouzid, T. Bentrcia, X. Ma, S. Djurović, L.H. Mouss, “Machine Learning-Based Condition Monitoring for PV Systems: State of the Art and Future Prospects,” Energies, vol. 14, pp. 6316, October 2021.
E. Demirel, “Study of Lightning Strike Activity in Solar Power Plants,” Master’s thesis, Muğla Sıtkı Koçman University Institute of Pure and Applied Sciences, Türkiye, March 2021.
L.B. Bosman, W.D. Leon-Salas, W. Hutzel, E.A. Soto, “PV System Predictive Maintenance: Challenges, Current Approaches, and Opportunities,” Energies, vol. 13, pp. 1398, March 2020.
A. Bhuvanesh, & M. Paul, & S. Mahalakshmi, & M. Karuppasamypandiyan, “Classification and Detection of Faults in Grid Connected Photovoltaic System,” International Journal of Printing, Packaging & Allied Sciences, vol. 4, pp. 2430-38, April 2016.
S. Rapaport & M. Green & P. Graniero & C. Ulbrich & A. Louwen & U. Jahn, “The Use of Advanced Algorithms in PV Failure Monitoring,” Technical Report, IEA-PVPS T13-19, 2022.
A. Appiah & X. Zhang & B. Ayawli & E.F. Kyeremeh, “Review and Performance Evaluation of Photovoltaic Array Fault Detection and Diagnosis Techniques,” International Journal of Photoenergy, pp. 1-19, February 2019.
F. Aziz, A. Ul Haq, S. Ahmad, Y. Mahmoud, M. Jalal and U. Ali, “A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays,” IEEE Access, vol. 8, pp. 41889-41904, March 2020.
B. Basnet & H. Chun & J. Bang, “An Intelligent Fault Detection Model for Fault Detection in Photovoltaic Systems,” Journal of Sensors, pp. 1-11, June 2020.
J. Arockia Dhanraj & A. Mostafaeipour & K. Velmurugan & K. Techato & P. Chaurasiya & J. Muthiya & A. Gopalan & K. Phoungthong, “An Effective Evaluation on Fault Detection in Solar Panels,” Energies, vol 14, pp. 7770, November 2021.
M, Köntges & S. Kurtz & C. Packard & U. Jahn & K. Berger & K. Kato & T. Friesen & H. Liu & M. Van Iseghem & J. Wohlgemuth & D. Miller & M. Kempe & P. Hacke & F. Reil & N. Bogdanski & W. Herrmann & C. Buerhop & G. Razongles & G. Friesen, “Review of Failures of Photovoltaic Modules,” March 2014.
L.D. Murillo-Soto, and C. Meza, “Detection Criterion for Progressive Faults in Photovoltaic Modules Based on Differential Voltage Measurements,” Applied Sciences, 12(5), pp. 2565, March 2022.
D. Ji & C, Zhang & M. Lv & Y. Ma & N. Guan, “Photovoltaic Array Fault Detection by Automatic Reconfiguration,” Energies, vol. 10, pp. 699., May 2017.
J. Oyekale, M. Petrollese, V. Tola, and G. Cau, “Impacts of Renewable Energy Resources on Effectiveness of Grid-Integrated Systems: Succinct Review of Current Challenges and Potential Solution Strategies,” Energies, 13(18), pp. 4856, 2020.
Y. Hong, R. A. Pula, “Methods of photovoltaic fault detection and classification: A review,” Energy Reports, vol. 8, pp. 5898-5929, 2022.
M. Arani & M. Akhavanhejazi, “The Comprehensive Study of Electrical Faults in PV Arrays,” Journal of Electrical and Computer Engineering, June 2016.
F. H. Gandoman & A. Ahmadi & A.M. Sharaf & P, Siano & J. Pou & B. Hredzak & V. Agelidis, “Review of FACTS technologies and applications for power quality in smart grids with renewable energy systems,” Renewable and Sustainable Energy Reviews, vol. 82, pp. 502–514., February 2018.
H. Liu & K. Xu & Z. Zhang & W. Liu & J. Ao, “Research on Theoretical Calculation Methods of Photovoltaic Power Short-Circuit Current and Influencing Factors of Its Fault Characteristics,” Energies, vol. 12, pp. 316, January 2019.
M. Eltawil & Z. Zhao, “Grid-connected photovoltaic power systems: Technical and potential problems—A review,” Renewable and Sustainable Energy Reviews, 14. 112-129, 2010.
S. Sarikh & R. Mustapha & A. Bennouna & A. Benlarabi & B. Ikken, “Fault Diagnosis in a Photovoltaic system through I-V Characteristics Analysis,” 9th International Conference on Renewable Energy, Hammamet, Tunisia, March 2018.
A. Kulshrestha & O. Mahela & M. Gupta & N. Gupta & N. Patel & T. Senjyu & M.S.S. Danish & M. Khosravy, “A Hybrid Protection Scheme Using Stockwell Transform and Wigner Distribution Function for Power System Network with Solar Energy Penetration,” Energies, July 2020.
A. Betti & M. Tucci & E. Crisostomi & A. Piazzi & S. Barmada & D. Thomopulos, “Fault Prediction and Early-Detection in PV Power Plants based on Self-Organizing Maps,” Sensors, December 2021.
A.E. Nieto-Vallejo & F. Ruiz & D. Patino, “Characterization of electric faults in photovoltaic array systems,” DYNA, vol. 86, pp. 54-63, September 2019.
A. Zúñiga & A. Baleia & J. Fernandes & P. Branco, “Classical Failure Modes and Effects Analysis in the Context of Smart Grid Cyber-Physical Systems,” Energies, vol. 13, March 2020.
R. Namani & S. Banerjee & S. Subramaniam & N. Babu, “A simplified method for fault detection and identification of mismatch modules and strings in a grid-tied solar photovoltaic system,” International Journal of Emerging Electric Power Systems, 21(4), August 2020.
S. K. Firth & K. J. Lomas & S. Rees, “A simple model of PV system performance and its use in fault detection,” Solar Energy, 84(4), 2010.
M. Khan & K. Khan & A. Khan & Z. Ahmad & S. Khan & A. Mohammed, “A model-based approach for detecting and identifying faults on the D.C. side of a P.V. system using electrical signatures from I-V characteristics,” PLOS ONE, 17, March 2022.
Y. Chaibi, M. Malvoni, A. Chouder, M. Boussetta, M. Salhi, “Simple and efficient approach to detect and diagnose electrical faults and partial shading in photovoltaic systems,” Energy Conversion and Management, vol. 196, pp. 330-343, September 2019.
S.A. Memon, Q. Javed, W.G. Kim, Z. Mahmood, U. Khan, M.A. Shahzad, “Machine-Learning-Based Robust Classification Method for PV Panel Faults,” Sensors, Nov 4, 2022.
B. Li, C. Delpha, D. Diallo, A. Migan-Dubois, “Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review,” Renewable and Sustainable Energy Reviews, vol. 138, March 2021.
M. Köntges, & G. Oreski & U. Jahn, “Assessment of PV Module Failures in the Field; Technical Report,” International Energy Agency Photovoltaic Power Systems Programme: IEA PVPS Task 13, May 2017.
A. Y. Jaen-Cuellar, D. A. Elvira-Ortiz, R. A. Osornio-Rios, and J. A. Antonino-Daviu, "Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review," Energies, 15(15), pp. 5404, 2022.
Z. Yang, N. Zhang, J. Wang, Y. Liu, L. Fu, “Improved non-symmetrical puzzle reconfiguration scheme for power loss reduction in photovoltaic systems under partial shading conditions,” Sustainable Energy Technologies and Assessments, 51(99), pp. 101934, 2022.
A.E. Majid, “Study of Photovoltaic (PV) Module Interconnections Failure Analysis and Reliability,” Doctoral thesis, University of Wolverhampton Faculty of Science and Engineering, UK, August 2021.
M. Dhimish, “Fault Detection and Performance Analysis of Photovoltaic Installations,” Doctoral thesis, University of Huddersfield, March 2018.
URN: https://sloi.org/urn:sl:tjoee81283
Copyright (c) 2023 Turkish Journal of Electromechanics and Energy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Indexed in:
