Manuscript Topics

The generation of electrical energy through photovoltaic (PV) modules represents a key solution to meet the growing global electricity energy demands, covering a wide range of applications, from small-scale installations to extensive industrial plants. This well-established technology plays a fundamental role in the transition to renewable energy sources.

In recent years, PV system optimization has evolved beyond cost reduction, focusing on improving efficiency and reliability through advanced monitoring and diagnostic techniques. Since a PV system's performance is intrinsically linked to its electrical behaviour, real-time analysis of electrical parameters and environmental conditions becomes essential for implementing preventive and predictive maintenance strategies that maximize system lifespan and return on investment.

This special issue aims to explore advances that add value to both researchers and industry professionals, promoting new methodologies for analysing PV system performance based on electrical and environmental parameters. Furthermore, it seeks to thoroughly investigate failure mechanisms, degradation, and electrical mismatches, encouraging the development of innovative techniques for early anomaly detection, as well as novel modelling and simulation approaches to optimize PV system design and operation.

Topics of interest:

Original contributions are invited on, but not limited to, the following topics:
• Fault detection in photovoltaic systems based on electrical signal and environmental parameter analysis.
• Analysis and proposals of original parameters for diagnostic purposes in PV systems
• Forecasting techniques for PV system maintenance
• Protection schemes for PV systems
• Modeling and simulation of photovoltaic system components
• Advanced monitoring methods for PV systems
• Real-time diagnostics in photovoltaic systems
• Harmonic analysis, voltage stability, and frequency stability in PV microgrids
• Parameter estimation of photovoltaic systems using artificial intelligence
• Digital twinning of PV power plants

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