New Approach for Tracking, Monitoring, and Diagnosing Faults in a Photovoltaic System in Real Time: An Experimental and Case Study

Leila Boucerredj; Ali Khechekhouche; Nadir Benalia; Abderrahmane Khechekhouche; Antonio Marcos de Oliveira Siqueira; Julio Cesar Costa Campos

doi:10.18540/jcecvl10iss9pp20283

Autores

Leila Boucerredj Department of Electronics and Automatics, PIMIS Laboratory, University of Guelma, Algeria https://orcid.org/0000-0002-8481-7725
Ali Khechekhouche Laboratory (LNTDL), Faculty of Technology, University of El Oued, Algeria https://orcid.org/0000-0001-8310-2384
Nadir Benalia Applied Automation and Industrial Diagnostics Laboratory, University of Djelfa, Algeria
Abderrahmane Khechekhouche Laboratory (LNTDL), Faculty of Technology, University of El Oued, Algeria https://orcid.org/0000-0002-7278-2625
Antonio Marcos de Oliveira Siqueira Universidade Federal de Viçosa, Brazil https://orcid.org/0000-0001-9334-0394
Julio Cesar Costa Campos Universidade Federal de Viçosa, Brazil https://orcid.org/0000-0002-9488-8164

DOI:

https://doi.org/10.18540/jcecvl10iss9pp20283

Palavras-chave:

Renewable energy, Photovoltaic installations, Real-time monitoring, Fault diagnosis, Energy yield, Anomaly detection.

Resumo

Photovoltaic installations have emerged as a cornerstone of sustainable energy production, playing a pivotal role in the global transition towards renewable sources of electricity. As the demand for clean energy surges, so too does the need for robust monitoring and diagnostic strategies to ensure the efficient operation of these systems. This study presents a novel methodology for the real-time tracking, monitoring, and diagnosing of faults in photovoltaic systems (PVSs), emphasizing their crucial role in sustainable energy production amid the global shift to renewable energy. The study was conducted in Guelma, Algeria, during the spring and summer seasons. The investigation utilized WatchPower simulation software over a 24-hour performance analysis of the photovoltaic system. On June 19, 2023, with a high temperature of 32°C, the system achieved a peak output power of 600W under optimal conditions, validating its efficiency in energy generation. The study also analyzed the effects of shading on energy output by comparing data from a shaded day on May 14, 2023, at 25°C, to an unshaded day on June 21, 2023, at 32°C, during peak sunlight hours from 9:00 AM to 2:15 PM, the period when sunlight is at its strongest. The results showed a significant drop in output power from 600W to 450W due to shading, underscoring the importance of real-time monitoring to detect performance inefficiencies. This research not only enhances operational reliability and maintenance strategies for PV systems but also demonstrates the effectiveness of integrating real-time data analytics to support decision-making in similar environments.