Fault Diagnosis for Photovoltaic Systems Based on Sensors
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: 30 June 2024 | Viewed by 868
Special Issue Editor
Interests: supervision of complex systems; fault detection and diagnosis; improvement of electrical distribution; reliability evaluation of distribution systems; microgrids and smartgrids; integration of renewable energies in distribution systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Photovoltaic (PV) systems can experience substantial damage that affects constituent materials such as metals, crystals, encapsulating polymers, and, especially, PV cells. Consequently, the PV plants will decrease their performance in terms of power generation capacity. Solar panels are exposed to high degradation due to outdoor operation. Therefore, a good combination of online predictive diagnosis techniques is required to improve performance and avoid failures leading to the interruption of power generation.
This Special Issue will focus on PV fault detection and classification techniques based on sensors, covering topics that include, but are not limited to, the following:
- Sensors and sensing strategies for fault detection and diagnosis of PV devices;
- Sensors and sensing strategies for PV system voltages, currents, energy, power, and other electrically relevant quantities;
- Sensors and sensing strategies for irradiance, temperature, and other weather-related quantities;
- IoT–PV sensors and applications;
- Smart PV sensors;
- PV sensor development and analysis;
- Advanced PV sensor characterization;
- Embedded implementation of sensors, preprocessing techniques, computational-oriented strategies, edge computing;
- Calibration, characterization, and testing procedures for PV-oriented sensors;
- Visual and thermal inspection fault diagnosis methods;
- Electrical-based fault diagnosis methods;
- Machine learning and soft-computing techniques for data processing, aggregation, filtering, and forecasting in PV systems and applications.
Prof. Dr. Eduardo Quiles
Guest Editor
Manuscript Submission Information
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Keywords
- PV modules
- PV plants
- smart PV sensors
- IRT sensors
- self-powering sensors
- calibration PV sensors
- IoT sensors
- predictive fault diagnosis
- fault detection and diagnosis methods
- machine learning methods
