Advanced Fault Detection and Diagnosis for Photovoltaic Systems

Dear Colleagues,

The current expansion, growth, and popularity of PV systems is driven not only by the urging need related to clean energy sources transition, but also by the attractive economic aspects of the solar power as prices are continuously decreasing.

Thus, it is very important to maintain the optimal operational conditions of the PV systems. Even small faults which are not detected in time can lead to a decrease in power production efficiency and economic losses, respectively. In the context of long-term economic assessment, the decrease in energy production below the guaranteed threshold of the manufacturer is particularly important. Depending on the nature of the fault, this can lead to component damage or even a malfunction of the entire system.

Currently, there are various approaches to PV system fault detection and diagnosis, which are necessary in minimizing their effects and taking the necessary actions. The different types of faults that can occur in PV systems consist of the following electrical faults, due to defective bypass diodes, open circuits in modules, arrays, or panels, faulty connections, disconnected modules or strings, inverter faults; thermal faults, due to shading, degradation, or PID; mechanical faults, due to the corrosion of different components or hail; or environmental faults, due to soiling, bird droppings, or the accumulation of dust. Each kind of fault interacts with the PV system in different ways. The appearance of one fault may indicate another as well, underlying the importance of detection and differentianting each kind of fault using appropriate approaches, investigation techniques, and measurements.

Because of the impact of faults on PV system performance, the development of new techniques for fault detection and diagnosis suitable for specific fault conditions and unknown or new faults are of the utmost importance. Fault detection offers the possibility to significantly reduce operational downtime, a timely diagnosis that is essential for restoring the optimal functionality and energy production of the entire PV system.

The potential of ongoing research not only enhances the reliability and efficiency of photovoltaic systems, but also facilitates the development of innovative approaches and technologies that can further optimize energy production and fault detection mechanisms.

In this Special Issue, research articles, reviews, and original contributions are welcome. Research areas may include, but are not limited to, the following:

1. Fast fault detection on-site PV systems assessment;
2. Aerial inspection of PV systems;
3. Thermography in PV systems fault detection;
4. Electroluminescence;
5. UV fluorescence;
6. Electrical signals based fault detection and diagnosis;
7. Automated systems for fault detection, diagnosis, and fast maintenance;
8. Embedded solutions based on sensors, preprocessing techniques, computational-oriented strategies, and edge computing;
9. Machine learning and artificial intelligence-based PV system fault detection;
10. Machine learning and soft-computing techniques for data processing, aggregation, filtering, and forecasting in PV systems and applications;
11. Digital twins in PV system fault detection;
12. Other methods for the fault detection, assessment, and diagnosis of PV systems.

Dr. Alexandru-Ionel Constantin
Dr. Lucia Andreea El-Leathey
Dr. Paula Anghelita
Dr. Andrzej Ordys
Guest Editors

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• photovoltaic systems
• monitoring system
• fault detection
• fault diagnosis
• automatic supervision
• online monitoring
• real-time monitoring