<![CDATA[The rapid development of renewable energy systems has accelerated research on the integration of digital technologies in photovoltaic (PV) systems, particularly in predictive maintenance and intelligent monitoring. This study aims to analyze the research trends, thematic structure, and future research opportunities related to digital twin applications in predictive maintenance for photovoltaic systems using a bibliometric approach. Data were collected from the Scopus database using the query: (“digital twin” AND (“predictive maintenance” OR “fault detection” OR “condition monitoring”) AND (“photovoltaic” OR “solar energy” OR “PV system” OR “bifacial photovoltaic” OR “bifacial PV”)). The study analyzed 60 selected documents published between 2020 and 2026 using the PRISMA approach and VOSviewer visualization. The results indicate a significant increase in scientific publications after 2023, from 1 publication in 2020, 2 in 2021, 2 in 2022, and 4 in 2023, to 13 publications in 2024 and a peak of 32 publications in 2025. The network visualization analysis revealed that the dominant research topics were digital twin, photovoltaic systems, predictive maintenance, fault detection, machine learning, artificial intelligence, and renewable energy. Overlay visualization further showed a research shift from conventional fault diagnosis toward intelligent real-time monitoring systems based on AI, IoT, and predictive analytics. In addition, the bibliometric mapping demonstrated that bifacial photovoltaic technology has not yet emerged as a dominant research cluster or keyword in the existing literature network. This finding indicates that the integration of digital twin and predictive maintenance into bifacial photovoltaic systems remains underexplored and represents a promising future research direction. This study contributes to identifying the evolution of research trends and the emerging opportunities for developing intelligent and sustainable photovoltaic systems based on digital twin technology. Keywords: Digital Twin, Predictive Maintenance, Photovoltaic Systems, Bibliometric Analysis, Renewable Energy, Bifacial Photovoltaic.]]>
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