Challenges and Methodological Innovations in Developing a Digital Twin for Photovoltaic Inverters

This study examines the complexities associated with developing a digital twin (DT) for photovoltaic (PV) inverters and presents a systematic strategy for addressing these challenges. It highlights the significant impact of digital twin modeling on improving maintenance approaches for PV systems by enabling predictive maintenance and early anomaly identification. In addition, the paper addresses the challenges encountered in implementing a digital twin for photovoltaic inverters, including the complexity of the data and systems involved, as well as the need for accurate real-time analysis. The proposed methodological framework addresses these challenges by integrating robust data management systems, model validation techniques and integration strategies to ensure accurate correlation between the digital twin and the performance of the physical inverter. This methodology aims to improve the reliability and functional efficiency of photovoltaic inverters in the context of extended renewable energy systems. Furthermore, this paper provides researchers and academics with a concise overview of the different approaches to the digital twin of photovoltaic inverters, presenting an in-depth analysis of its complexities, challenges and potential impact on the progress of inverter research.