A Novel Architecture and Estimation Algorithm for Adaptive Distribution Phasor Measurement Unit in Renewable-Rich Electrical Distribution System

Sensing and measurement devices are keeping pace with advancements in the distribution power system. The ability to provide time-synchronized measurements at a fast reporting rate by distribution-Phasor Measurement Units (D-PMUs), especially with increasing distributed renewable energy resources (DRERs), offers great opportunities. However, unlike the transmission systems, distribution system waveforms typically exhibit more noise, harmonics, and unbalanced phases, posing unique challenges in estimating phasors at the distribution level. The lack of specific standards for the performance requirements of D-PMUs makes this challenge even more significant. This work proposes a novel D-PMU architecture and phasor estimation algorithm in presence of polluted signals. The proposed sensor architecture is adaptive to varying system operating conditions and can adjust reporting rates based on application requirements. The proposed approach employs a Sliding Fast Fourier Transform (SFFT) and Signal Estimation by Minimizing Parameter Residuals (SEMPR) technique to simultaneously estimate the harmonic components along with the fundamental phasor. Furthermore, to accommodate signals generated from varying system conditions in the distribution system, proposed approach updates the measurement model for DPMU estimation using adaptive filtering and a goodness-of-fit (GoF) measure. It is demonstrated that the proposed architecture can accurately estimate the phasor and harmonic components for time-varying distorted distribution signals for a specific example application.