Operational Performance, Degradation and Reliability of Photovoltaic Systems

Dear Colleagues,

In today’s energy sector, the deployment of renewables is increasing, and their contribution is vital to the energy transition. The key drivers of the renewable-based energy transition are increased energy demands, fossil fuel prices, and concerns related to greenhouse gas emission. Because of these concerns, there has been a tremendous increase in the use of renewables for energy requirements at various levels and in numerous applications. In particular, photovoltaic (PV) systems have been rapidly growing all over the world in recent years, due mainly to the beneficial effects on price reduction. On the other hand, the improvements seen in the materials and development of components (advanced solar energy materials, solar cells, converters, batteries) related to PV systems are quite promising. These developments contribute to PV system performance improvements, but the questions related to their long-term performance and reliability are still not clear. We believe that advanced monitoring techniques and regular diagnostics of PV systems could significantly improve performance. Applying these techniques will enable us to have clear understanding over the operating condition by ensuring high reliability of the solar power systems (broadly classified as off-grid and on-grid installation). At present, the solar energy systems and their installations are seen in numerous configurations, such as ground mount, floating, submerged, solar trees, space-based solar PVs, etc. In each configuration, the performance would be different as the operating behavior would change. For example, the degradation and reliability behavior of a PV system and its components would vary with respect to the configuration, due to the medium of installation and type of weather conditions the PV module experiences. The variation in performance due to degradation and reliability has a direct effect on the economic viabilities of such PV installations. Hence, having a clear understanding of such variations would lead to a positive impact on the investment cost and levelized cost of energy (LCOE), making such systems competitive and more sustainable. This can be achieved by improving the reliability and service lifetime performance through advanced monitoring, enhanced data analytic methods, early failure detection and classification, degradation rate estimation, and accurate PV production forecasting in different climates.

The purpose of this Special Issue is to study and explore various methods and tools to understand the operational behavior, performance degradation, and reliability of photovoltaic systems. In addition, it also seeks to understand the relation of solar photovoltaic systems degradation and reliability in the context of economic sustainability.

This Special Issue seeks outstanding research articles, case study articles, review articles, short communications, and perspective articles in topics that include but are not limited to the following:

• Degradation rate estimation procedures;
• Light-induced and potential-induced degradation studies in PV systems;
• PV module structural degradation mechanisms;
• Analysis of degradation inspection techniques applicable to PV power plants;
• Performance modeling of PV systems;
• Reliability modeling of PV systems;
• Energy loss investigations of PV systems;
• Modeling of the various losses of PV systems and their effect on performance;
• Soiling effect on the degradation;
• Effect of temperature on degradation;
• Fault and failures observed in PV systems;
• Novel photovoltaic installation methods and associated performance issues;
• Effect of weather conditions on PV component reliability;
• Role of machine learning and advanced data analytics in fault diagnostics of PV systems;
• Energy forecasting studies;
• Day-ahead and year-ahead energy and degradation estimation;
• Early fault and failure detection methods;
• Resilience of PV systems due to disruptions;
• Effect of degradation on the cost of electricity, revenues generated by multimegawatt PV projects;
• Environmental and/or economic impacts of the energy production process, lifecycle assessment (LCA), and lifecycle cost (LCC).

References:

Kumar, N. M., & Malvoni, M. (2019). A preliminary study of the degradation of large-scale c-Si photovoltaic system under four years of operation in semi-arid climates. Results in Physics, 12, 1395-1397.

Malvoni, M., De Giorgi, M. G., & Congedo, P. M. (2017). Study of degradation of a grid connected photovoltaic system. Energy Procedia, 126, 644-650.

Kumar, N. M., Gupta, R. P., Mathew, M., Jayakumar, A., & Singh, N. K. (2019). Performance, energy loss, and degradation prediction of roof-integrated crystalline solar PV system installed in Northern India. Case Studies in Thermal Engineering, 13, 100409.

Kumar, N. M., Prabaharan, N., & Jerin, A. R. A. (2019). Impact of Performance Degradation and Capital Subsidy on the Revenue of Rooftop Solar PV System. International Journal of Renewable Energy Research (IJRER), 9(1), 128-136.

Tahri, A., Silvestre, S., Tahri, F., Benlebna, S., & Chouder, A. (2017). Analysis of thin film photovoltaic modules under outdoor long term exposure in semi-arid climate conditions. Solar Energy, 157, 587-595.

Silvestre, S., Tahri, A., Tahri, F., Benlebna, S., & Chouder, A. (2018). Evaluation of the performance and degradation of crystalline silicon-based photovoltaic modules in the Saharan environment. Energy, 152, 57-63.

Silvestre, S., Kichou, S., Guglielminotti, L., Nofuentes, G., & Alonso-Abella, M. (2016). Degradation analysis of thin film photovoltaic modules under outdoor long term exposure in Spanish continental climate conditions. Solar Energy, 139, 599-607.

Kichou, S., Silvestre, S., Nofuentes, G., Torres-Ramírez, M., Chouder, A., & Guasch, D. (2016). Characterization of degradation and evaluation of model parameters of amorphous silicon photovoltaic modules under outdoor long term exposure. Energy, 96, 231-241.

Pei, T., & Hao, X. (2019). A Fault Detection Method for Photovoltaic Systems Based on Voltage and Current Observation and Evaluation. Energies, 12(9), 1712.

Vergura, S. (2018). Hypothesis tests-based analysis for anomaly detection in photovoltaic systems in the absence of environmental parameters. Energies, 11(3), 485.

Chine, W., Mellit, A., Lughi, V., Malek, A., Sulligoi, G., & Pavan, A. M. (2016). A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks. Renewable Energy, 90, 501-512.

Papaelias, M., Cheng, L., Kogia, M., Mohimi, A., Kappatos, V., Selcuk, C., ... & Gan, T. H. (2016). Inspection and structural health monitoring techniques for concentrated solar power plants. Renewable Energy, 85, 1178-1191.

Walczak, M., Pineda, F., Fernandez, A. G., Mata-Torres, C., & Escobar, R. A. (2018). Materials corrosion for thermal energy storage systems in concentrated solar power plants. Renewable and Sustainable Energy Reviews, 86, 22-44.

Dr. Maria Malvoni
Dr. Nallapaneni Manoj Kumar
Guest Editors

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