Dynamic Symmetrical Sequence Decomposition Power Components for Disturbance Event Characterization

As modern technology is integrated into the legacy electric power grid, new power quality challenges arise in the distribution sector. Customer loads are becoming more sensitive to power quality events such as voltage sags, swells, and frequency variations. Moreover, an increasing prominence of non-linear loads is leading to higher harmonic distortion and equipment malfunctions. These complications, in addition to the expanding integration of distributed resources, emphasize the need for comprehensive power quality analysis. Defining clear, time-dependent metrics that capture the system's behavior is of significance. In this work, the Symmetrical Sequence Decomposition (SSD) methodology is developed for dynamic Fourier phasors to produce power metrics that capture disturbance characteristics of time-variant waveforms. The significance of these indicators is first demonstrated for simulated cases and is subsequently evaluated for real-world events for further classification. Negative- and zero-sequence power signatures are generated to indicate the onset, duration, and nature of disturbances.