A Review of Photovoltaic DC Systems Prognostics and Health Management: Challenges and Opportunities



Abbas Chokor Mounir El Asmar Sumanth V. Lokanath


The surge in renewable electricity generation using photovoltaic (PV) systems was accompanied by an increased awareness of the fault conditions developing during the operational lifetime. Fault detection, diagnostics, and prognostics are such efforts to detect and classify a fault so the system operational expectations can be managed. Trending of the faults and prognostics also aid to evaluate expected remaining useful life so that mitigation actions can be evaluated and implemented. This paper aims to review the state of the art and practice of prognostics and health management (PHM) for the DC side of PV systems. Following a review of the PV industry current status, the study describes and classifies the different failure modes. Next, it summarizes the PV faults detection, diagnostics and prognostics approaches. A review of the PHM applications for PV systems paves the way to emphasize the key research gaps and challenges in the current practice. The available opportunities are also highlighted through a comprehensive understanding of the PV systems current performance, from where scholars and decision makers can integrate improvement strategies with promising directions for future research and practices.

How to Cite

Chokor, A., El Asmar, M., & Lokanath, S. V. (2016). A Review of Photovoltaic DC Systems Prognostics and Health Management: Challenges and Opportunities. Annual Conference of the PHM Society, 8(1). https://doi.org/10.36001/phmconf.2016.v8i1.2505
Abstract 133 | PDF Downloads 149



prognostics, diagnostics, PHM, Review, Photovoltaics

Adinoyi, M., & Said, S. (2013). Effect of dust accumulation on the power outputs of solar photovoltaic modules. Renewable Energy, 60, 633-636.
Alam, M., Khan, F., Johnson, J., & Flicker, J. (2015). A Comprehensive Review of Catastrophic Faults in PV Arrays: Types, Detection, and Mitigation Techniques. IEEE Journal of Photovoltaics, 5 (3), 982-997.
Alam, M., Khan, F., Johnson, J., & Flicker, J. (2013). PV faults: Overview, modeling, prevention and detection techniques. IEEE 14th Workshop on Control and Modeling for Power Electronics (COMPEL).
Ancuta, F., & Cepisca, C. (2011). Fault analysis possibilities for PV panels. Proceedings of the 2011 3rd International Youth Conference on Energetics (IYCE).
Bower, W., & Wiles, J. (1994). Analysis of grounded and ungrounded photovoltaic systems. IEEE Photovoltaic Specialists Conference.
Braun, H., Banavar, M., & Spanias, A. (2012). Signal Processing for Solar Array Monitoring, Fault Detection, and Optimization. Morgan & Claypool Publishers.
Braun, H., Buddha, S., Krishnan, V., Spanias, A., Tepedelenlioglu, C., Yeider, T., & al. (2012). Signal processing for fault detection in photovoltaic arrays. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Chao, K. (2010). A novel fault diagnosis method based-on modified neural networks for photovoltaic systems. In Advances in Swarm Intelligence (pp. 531-539). Springer Berlin Heidelberg.
Chao, K., Ho, S., & Wang, M. (2008). Modeling and fault diagnosis of a photovoltaic system. Electric Power Systems Research, 78 (1), 97-105.
Charki, A., Laronde, R., & Bigaud, D. (2013). Accelerated degradation testing of a photovoltaic module. Journal of Photonics for Energy, 3 (1).
Cheng, Z., Zhong, D., Li, B., & Liu, Y. (2011). Research on fault detection of PV array based on data fusion and fuzzy mathematics. Power and Energy Engineering Conference.
Chouder, A., & Silvestre, S. (2010). Automatic supervision and fault detection of PV systems based on power losses analysis. Energy Conversion and Management, 51 (10), 1929-1937.
Chuang, S., Ishibashi, A., Kijima, S., Nakayama, N., Ukita, M., & Taniguchi, S. (1997). Kinetic model for degradation of lightemitting diodes. IEEE Journal of Quantum electronics, 33, pp 970–979.
Cocca, M., D’Arienzo, L., & D’Orazio, L. (2011). Effects of Different Artificial Agings on Structure and Properties of Whatman Paper Samples. Materials Science, ID 863083.
Coleman, A., & Zalewski, J. (2011). Intelligent fault detection and diagnostics in solar plants. Intelligent Data Acquisition and Advanced Computing Systems (IDAACS).
Collier, D., & Key, T. (1988). Electrical fault protection for a large photovoltaic power plant inverter. IEEE Photovoltaic Specialists Conference.
Cristaldi, L., Faifer, M., Lazzaroni, M., Khalil, A., Catelani, M., & Ciani, L. (2014). Failure modes analysis and diagnostic architecture for photovoltaic plants. Proccedings of the 13 the IMEKO TC10 Workshop on Technical Diagnostics Advanced measurement tools in technical diagnostics for systems’ reliability and safety.
Cristaldi, L., Faifer, M., Lazzaroni, M., Khalil, A., Catelani, M., & Ciani, L. (2014). Failure modes analysis and diagnostic architecture for photovoltaic plants. IMEKO TC10 Workshop on Technical Diagnostics Advanced measurement tools in technical diagnostics for systems’ reliability and safety.
Dini, D., Brazis, P., & Yen, K. (2011). Development of arc-fault circuit-interrupter requirements for photovoltaic systems. IEEE Photovoltaic Specialists Conference (PVSC).
Drews, A., De Keizer, A., Beyer, H., Lorenz, E., Betcke, J., Van Sark, W., & al. (2007). Monitoring and remote failure detection of grid-connected PV systems based on satellite observations. Solar Energy, 81 (4), 548-564.
Ducange, P., Fazzolari, M., Lazzerini, B., & Marcelloni, F. (2011). An intelligent system for detecting faults in photovoltaic fields. Intelligent systems design and applications (ISDA).
Dumas, L., & Shumka, A. (1982). Photovoltaic module reliability improvement through application testing and failure analysis. IEEE Transactions on Reliability, 31 (3), 228-234.
Escobar, L. & Meeker, W. (2006). A review of accelerated test models. Statistical Science, 21 (4), 552–577.
Firth, S., Lomas, K., & Rees, S. (2010). A simple model of PV system performance and its use in fault detection. Solar Energy , 84 (4), 624-635.
Flicker, J., & Johnson, J. (2013). Electrical simulations of series and parallel. 39th IEEE Photovoltaic Specialist Conference.
Gokmen, N., Karatepe, E., Celik, B., & Silvestre, S. (2012). Simple diagnostic approach for determining of faulted PV modules in string based PV arrays. Solar Energy, 86 (11), 3364-3377.
Gokmen, N., Karatepe, E., Silvestre, S., Celik, B., & Ortega, P. (2013). An efficient fault diagnosis method for PV systems based on operating voltage-window. Energy Conversion and Management , 73, 350-360.
Hammond, R., Srinivasan, D., Harris, A., Whitfield, K., & Wohlgemuth, J. (1997). Effects of soiling on PV module and radiometer performance. Photovoltaic Specialists Conference.
Hare, J., Shi, X., Gupta, S., & Bazzi, A. (2016). Fault diagnostics in smart micro-grids: A survey. Renewable and Sustainable Energy Reviews , 60, 1114-1124.
Hastings, J., Juds, M., Luebke, C., & Pahl, B. (2011). A study of ignition time for materials exposed to DC arcing in PV systems. 37th IEEE Photovoltaic Specialists Conference.
Heng, A., Zhang, S., Tan, A., & Mathew, J. (2009). Rotating machinery prognostics: State of the art, challenges and opportunities. Mechanical Systems and Signal Processing, 23(3), 724-739.
Houssein, A., Heraud, N., Souleiman, I., & Pellet, G. (2010). Monitoring and fault diagnosis of photovoltaic panels. IEEE Energy Conference and Exhibition (EnergyCon).
Hu, Y., Gao, B., Song, X., Tian, G., Li, K., & He, X. (2013). Photovoltaic fault detection using a parameter based model. Solar Energy , 96, 96-102.
Jeong, J., & Park, N. (2013). Field discoloration analysis and UV/temperature accelerated degradation test of EVA for PV. Photovoltaic Specialists Conference (PVSC).
Jiang, H., Lu, L., & Sun, K. (2011). Experimental investigation of the impact of airborne dust deposition on the performance of solar photovoltaic (PV) modules. Atmospheric Environment, 45 (25), 4299-4304.
Jiang, L., & Maskell, D. (2015). Automatic fault detection and diagnosis for photovoltaic systems using combined artificial neural network and analytical based methods. International Joint Conference on Neural Networks (IJCNN).
Johnson, J., Kuszmaul, S., Bower, W., & Schoenwald, D. (2011). Using PV module and line frequency response data to create robust arc fault detectors. Proceedings of the 26th European Photovoltaic Solar Energy Conference and Exhibition.
Johnson, J., Schoenwald, D., Kuszmaul, S., Strauch, J., & Bower, W. (2011). Creating dynamic equivalent PV circuit models with impedance spectroscopy for arc fault modeling. Photovoltaic Specialists Conference (PVSC).
Kalogirou, S., & Tripanagnostopoulos, Y. (2007). Industrial application of PV/T solar energy systems. Applied Thermal Engineering , 27 (8), 1259-1270.
Kaplani, E. (2012). Detection of degradation effects in field-aged c-Si solar cells through IR thermography and digital image processing. International Journal of Photoenergy.
Katiraei, F., & Agüero, J. (2011). Solar PV integration challenges. Power and Energy Magazine , 9 (3), 62-71.
Kaushik, A., & Golnas, A. (2011). PV system reliability: lessons learned from a fleet of 333 systems. SPIE Solar Energy and Technology. International Society for Optics and Photonics.
Kempe, M. (2005). Control of moisture ingress into photovoltaic modules. Photovoltaic Specialists Conference.
Kojima, T., & Yanagisawa, T. (2004). The evaluation of accelerated test for degradation a stacked a-Si solar cell and EVA films. Solar Energy Materials & Solar Cells, 81 (1), 119–123.
Laidler, K. (1984). The development of the Arrhenius equation. Journal of Chemical Education, 61 (6), 494-498.
Li, Z., Wang, Y., Zhou, D., & Wu, C. (2012). An intelligent method for fault diagnosis in photovoltaic array. System Simulation and Scientific Computing.
Lin, X., Wang, Y., Zhu, D., Chang, N., & Pedram, M. (2012). Online fault detection and tolerance for photovoltaic energy harvesting systems. Proceedings of the International Conference on Computer-Aided Design.
Manganiello, P., Balato, M., & Vitelli, M. (2015). A survey on mismatching and aging of PV modules: The closed loop. IEEE Transactions on Industrial Electronics, 62 (11), 7276-7286.
Marion, B., & Adelstein, J. (2003). Long-term performance of the SERF PV systems. NCPV and Solar Program Review Meeting.
Molenbroek, E., Waddington, D., & Emery, K. (1991). Hot spot susceptibility and testing of PV modules. Photovoltaic Specialists Conference.
Ndiaye, A., Charki, A., Kobi, A., Kébé, C., Ndiaye, P., & Sambou, V. (2013). Degradations of silicon photovoltaic modules: A literature review. Solar Energy , 96, 140-151.
Nguyen, D., & Lehman, B. (2006). Modeling and simulation of solar PV arrays under changing illumination conditions. IEEE Workshops on Computers in Power Electronics.
Nilsson, D. (2014). Fault detection in photovoltaic systems. KTH Royal Institute of Technology, Master's Thesis.
Obi, M., & Bass, R. (2016). Trends and challenges of grid-connected photovoltaic systems–A review. Renewable and Sustainable Energy Reviews , 58, 1082-1094.
Oreski, G., & Wallner, G. (2005). Aging mechanisms of polymeric films for PV encapsulation. Solar Energy, 79, 612–617.
Oreski, G., & Wallner, G. (2010). Damp heat induced physical aging of PV encapsulation materials. 12th IEEE Intersociety Conference on. Thermal and Thermo-Mechanical Phenomena in Electronic Systems.
Osterwald, C., Benner, J., Pruett, J., Anderberg, A., Rummeland, S., & Ottoson, L. (2003). Degradation in weathered crystalline-silicon PV modules apparently caused by UV radiation. The 3rd World Conference on Photovoltaic Energy Conversion, Osaka, Japan, pp. 2911– 2915.
Pan, R., Kuitche, J., & Tamizhmani, G. (2011). Degradation analysis of solar photovoltaic modules: Influence of environmental factor. Annual Reliability and Maintainability Symposium.
Patel, H., & Agarwal, V. (2008). “MATLAB-Based modeling to study the effects of partial shading on PV array characteristics. IEEE Transactions on Energy Conversion, 23 (1), 302-310.
Phinikarides, A., Kindyni, N., Makrides, G., & Georghiou, G. (2014). Review of photovoltaic degradation rate methodologies. Renewable and Sustainable Energy Reviews, 40, 143-152.
Polo, F., Del Rosario, J., & García, G. (2010). Supervisory control and automatic failure detection in grid-connected photovoltaic systems. Trends in Applied Intelligent Systems.
Quaschning, V., & Hanitsch, R. (1996). Numerical simulation of current-voltage characteristics of photovoltaic systems with shaded solar cells. Solar Energy , 56 (6).
Quintana, M., King, D., McMahon, T., & Osterwald, C. (2002). Commonly observed degradation in field-aged photovoltaic modules. Photovoltaic Specialists Conference.
Raghuraman, B., Laksman, V., Kuitche, J., Shisler, W., Tamizhani, G., & Kapoor, H. (2006). An overview of SMUDs outdoor photovoltaic test program at Arizona State University. IEEE World Conference on Photovoltaic Energy Conversion, Hawaii, USA.
Rauschenbach, H., & Maiden, E. (1972). Breakdown phenomena in reverse biased silicon solar cells. IEEE Photovoltaic Specialists Conference.
Syafaruddin, S. & Karatepe, E. (2011). Controlling of artificial neural network. Intelligent System Application to Power Systems (ISAP).
Saly, V., Ruzinsky, M., Packa, J., & Redi, P. (2002). Examination of solar cells and encapsulations of small experimental photovoltaic modules. 2nd International IEEE Conference on Polymers and Adhesives in Microelectronics and Photonics.
Schimpf, F., & Norum, L. (2009). Recognition of electric arcing in the DC-wiring of photovoltaic systems. International Telecommunications Energy Conference.
Schirone, L., Califano, F., Moschella, U., & Rocca, U. (1994). Fault finding in a 1 MW photovoltaic plant by reflectometry. Photovoltaic Energy Conversion, IEEE Photovoltaic Specialists Conference.
Sharma, N., & Dalal, D. (2015). Efficiency and Result Analysis of 50Kw Grid Connected PV System Using MATLAB/SIMULINK. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering , 4 (10), 8200-8206.
Silvestre, S., Chouder, A., & Karatepe, E. (2013). Automatic fault detection in grid connected PV systems. Solar Energy , 94, 119-127.
Skoczek, A., Sample, T., & Dunlop, E. (2009). The results of performance measurements of field‐aged crystalline silicon photovoltaic modules. Progress in Photovoltaics: Research and Applications , 17 (4), 227-240.
Solórzano, J., & Egido, M. (2013). Automatic fault diagnosis in PV systems with distributed MPPT. Energy Conversion and Management , 76, 925-934.
Spagnuolo, G., Xiao, W., & Cecati, C. (2015). Monitoring, Diagnosis, Prognosis, and Techniques for Increasing the Lifetime/Reliability of Photovoltaic Systems. IEEE Transactions Industrial Electronics, 62 (11), 7226-7227.
Spertino, F., & Akilimali, J. (2009). Are Manufacturing–Mismatch and Reverse Currents Key Factors in Large Photovoltaic Arrays? IEEE Transactions on Industrial Electronics, 56 (11), 4520-4531.
Stellbogen, D. (1993). Use of PV circuit simulation for fault detection in PV array fields. IEEE Photovoltaic Specialists Conference.
Takashima, T., Yamaguchi, J., & Ishida, M. (2008a). Disconnection detection using earth capacitance measurement in photovoltaic module string. Progress in Photovoltaics: Research and Applications , 16 (8), 669-677.
Takashima, T., Yamaguchi, J., & Ishida, M. (2008b). Fault detection by signal response in PV module strings. IEEE Photovoltaic Specialists Conference.
Takashima, T., Yamaguchi, J., Otani, K., Kato, K., & Ishida, M. (2006). Experimental studies of failure detection methods in PV module strings. IEEE 4th World Conference on Photovoltaic Energy Conversion.
Vazquez, M., Ignacio, R.S., 2008. Photovoltaic module reliability model based on field degradation studies. Progress in Photovoltaics: Research and Applications, 16, 419–433.
Vergura, S., Acciani, G., Amoruso, V., & Patrono, G. (2008). Inferential statistics for monitoring and fault forecasting of PV plants. IEEE International Symposium on Industrial Electronics.
Wohlgemuth, J., & Kurtz, S. (2011). Reliability testing beyond Qualification as a key component in photovoltaic progress toward grid parity. IEEE International Reliability Physics Symposium (IRPS).
Xie, J., & Pecht, M. (2003). Reliability prediction modelling of semiconductor light emitting device. IEEE Transactions on Device and Materials Reliability 3, 218–222.
Xu, X., Wang, H., & Zuo, Y. (2011). Method for diagnosing photovoltaic array fault in solar photovoltaic system. Power and Energy Engineering Conference (APPEEC).
Zhao, Y., Ball, R., Mosesian, J., De Palma, J., & Lehman, B. (2015). Graph-based semi-supervised learning for fault detection and classification in solar photovoltaic arrays. IEEE Transactions on Power Electronics, 30 (5), 2848-2858.
Zhao, Y., De Palma, J., Mosesian, J., Lyons, R., & Lehman, B. (2013). Line–line fault analysis and protection challenges in solar photovoltaic arrays. IEEE Transactions on Industrial Electronics, 60 (9), 3784-3795.
Zhao, Y., Lehman, B., De Palma, J., Mosesian, J., & Lyons, R. (2011). Fault analysis in solar PV arrays under: Low irradiance conditions and reverse connections. Photovoltaic Specialists Conference (PVSC).
Zhao, Y., Lehman, B., De Palma, J., Mosesian, J., & Lyons, R. (2011). Fault analysis in solar PV arrays under: Low irradiance conditions and reverse connections. Photovoltaic Specialists Conference (PVSC).
Zhao, Y., Yang, L., Lehman, B., De Palma, J., Mosesian, J., & Lyons, R. (2012). Decision tree-based fault detection and classification in solar photovoltaic arrays. Applied Power Electronics Conference and Exposition (APEC).
Zhiqiang, H., & Li, G. (2009). Research and implementation of microcomputer online fault detection of solar array. International Conference on Computer Science & Education.
Zhou, E. (2015). US Renewable Energy Policy and Industry, National Renewable Energy Laboratory (NREL).
Zimmerman, C. (2008). Time dependent degradation of photovoltaic modules by ultraviolet light. Applied Physics Letter.
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