Enhanced Online Impedance Estimation of Grid-Connected Inverter Using Hybrid Pseudorandom Binary Sequence

As renewable energy sources increasingly become part of the electrical grid, the need for advanced monitoring and control systems is more pressing than ever. One critical component is the online impedance estimation of grid-connected inverters, a key factor in ensuring system stability, control, and low-voltage ride-through capabilities. Existing techniques for impedance measurement are generally divided into non-intrusive and intrusive methods, each with its own set of challenges and limitations. This paper presents a groundbreaking approach to online impedance estimation using a Hybrid Pseudo-random Binary Sequence (HPRBS). Unlike conventional Pseudo-Random Binary Sequence (PRBS), which is character-ized by low power content in the low-frequency region, the proposed method exhibits reduced susceptibility to noise. The HPRBS method is engineered for robustness in noisy environments and offers enhanced grid impedance measurement. The proposed HPRBS framework strikes a balance between ease of implementation and measurement accuracy, offering a practical and reliable solution for real-time impedance assessment in grid-connected inverters. This innovative approach has the potential to significantly improve the reliability and efficiency of integrating renewable energy sources into the electrical grid.