Artificial Intelligence Technologies Applied in Photovoltaic Systems

Dear Colleagues,

Artificial intelligence (AI) has rapidly emerged as a transformative technology for photovoltaic (PV) systems, enabling intelligent solutions throughout the entire lifecycle of solar energy generation. Recent advances in machine learning, deep learning, reinforcement learning, computer vision, digital twins and data-driven optimization have significantly enhanced the capability of PV systems to operate more efficiently, reliably and autonomously under diverse environmental and operational conditions. AI technologies are increasingly being applied to improve PV system design, energy forecasting, fault diagnosis, predictive maintenance, performance assessment, operation, control and grid integration, thereby supporting the continued expansion of renewable energy deployment.

This Special Issue aims to provide an interdisciplinary platform for researchers, engineers and practitioners to present the latest advances in artificial intelligence technologies applied to photovoltaic systems. Original research articles, review papers and case studies addressing both theoretical developments and practical implementations are welcome. Particular emphasis is placed on innovative AI methodologies that improve the intelligence, resilience, efficiency, reliability and sustainability of photovoltaic systems across residential, commercial, industrial, utility-scale, floating, building-integrated, agrivoltaic and emerging PV applications.

Topics of interest include, but are not limited to, the following:

• Artificial intelligence and machine learning for photovoltaic systems
• Deep learning and data-driven modelling for solar energy applications
• Solar irradiance and photovoltaic power forecasting
• AI-assisted photovoltaic system design and optimization
• Intelligent maximum power point tracking (MPPT)
• AI-assisted solar tracking and tracking optimization
• Fault diagnosis, anomaly detection and predictive maintenance
• Computer vision for photovoltaic inspection and condition monitoring
• Photovoltaic performance assessment and degradation prediction
• Digital twins for photovoltaic systems
• Internet of Things (IoT), edge AI and intelligent sensing for PV applications
• AI-based energy management and photovoltaic–battery systems
• Smart inverter control and grid integration of photovoltaic systems
• Explainable artificial intelligence (XAI) and trustworthy AI for photovoltaic applications
• AI-assisted operation, maintenance and decision support for photovoltaic systems
• Techno-economic assessment and optimization of AI-enabled photovoltaic systems

Prof. Dr. Boon Han Lim
Dr. Ming Hui Tan
Guest Editors

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