A review of signal processing for fault diagnosis in systems with inverter-based resources and an improved high-frequency component-based disturbance detector

Given the growing penetration of Inverter-Based Resources (IBRs) in modern power systems and their impacts on traditional fault diagnosis functions, this paper reviews the performance of 133 variations of signal processing techniques, aiming to highlight those that present the most significant potential for new applications related to disturbance detection in systems with IBRs. The assessments simultaneously consider the processing time, stability under steady-state conditions, and sensitivity for grid disturbance detection. Based on such analysis, a new parameter-free and high-frequency component-based disturbance detector is proposed, which operates based on a self-adjusting threshold that does not require previous studies by the user to work. The proposed method is detailed and compared to state-of-the-art techniques. For such studies, a typical topology of IBR interconnection to the primary grid is modeled in the PSCAD software, assuming different IBR control grid code requirements, grid short-circuit levels, and contingency scenarios on the interconnection line. Besides proving the superiority of the proposed method, the results highlight the signal processing techniques with the most significant potential for detecting short and fast transients in systems with IBRs.