Digital Twin Framework for 1-Phase Grid-Tied PV System: A Frequency Domain Modeling and E2FD-HO-Based Approach for Power Electronic Circuits
Arun Kumar, Nishant Kumar
Abstract
This paper introduces a smart Digital Twin (DT) framework for a single-phase grid-integrated solar photovoltaic (SPV) inverter system that ensures advanced fault diagnostics and optimized operational performance. The DT is mathematically formalized using state-space equations modelling, functioning as a virtual counterpart to the physical system (PS). Real-time synchronization is achieved through high-fidelity sensor data acquisition within PS, enabling continuous monitoring and adaptive control. A rigorously formulated objective function, integrating empirical PS data and mathematically inferred parameters, underpins the optimization process, ensuring a superior digital representation. The critical system parameters, including ON-state resistance variations of switches, capacitance drifts, and inductor losses, are dynamically calibrated through an Electrostatic & Electromagnetic Field Discharge-Hybrid Optimization (E2FD-HO), a physics-driven optimization algorithm. The DT not only enables data-driven fault diagnostics but also proactively mitigates operational instabilities through real-time predictive control strategies. The control for the system is implemented within the FPGA-based controller (NI-sbRIO-9636) and the proposed DT framework is implemented on the OPAL-RT setup. The results of DT in comparison to hardware results of PS demonstrate an exceptional percentage matching score (PSM) of DT & PS, above than 98.5%, confirms its robustness and predictive precision. The developed DT offers a transformative approach to SPV inverter diagnosis, advancing circuit-level intelligence in smart energy systems.