Deepthi Pilakkat, Karthi Balasubramanian, Sree Ranjani Rajendran
As the deployment of photovoltaic (PV) systems accelerates globally, the demand for intelligent, real-time energy management solutions has grown. Digital Twin (DT) technology, which creates dynamic, synchronized virtual replicas of physical PV assets, has proven valuable for monitoring and basic control. However, most current DT-PV implementations are confined to data visualization, fault detection, or offline simulations, lacking capabilities for predictive control, cyber-physical security, and energy storage integration. This survey critically reviews the emerging role of DTs beyond monitoring, focusing on three key areas: (i) predictive control frameworks, including real-time inverter regulation and maximum power point tracking (MPPT) coordination; (ii) cybersecurity mechanisms within DT-enabled PV systems, such as anomaly detection, threat mitigation, and secure IoT protocols; and (iii) integration of battery storage into DT models for state-of-charge estimation and co-optimization. While significant progress is noted in predictive control and grid-interfaced DT applications, the use of DT for guiding MPPT and coordinating energy storage remains in a nascent stage. Using a PRISMA-style review methodology, this survey synthesizes recent advances across PV and related energy domains, this work identifies key gaps, transferable innovations, and outlines a future research roadmap toward scalable, secure, and intelligent DT-PV systems.