Residential Harmonic Injection Models Based on Field Measurements

Abstract

In recent years, harmonic current levels have increased in residential distribution networks due to the growing penetration of nonlinear loads at customer premises. To properly model the harmonic current injection of residences, probabilistic models that account for the stochastic behavior of domestic loads are needed. As a part of the study reported in this paper, a field measurement campaign was performed in 24 dwellings during a one-week period with a one-minute resolution. Harmonic current magnitudes and phase angles of odd harmonic orders up to the 25th as well as the active and reactive power demanded were recorded. By applying two different unsupervised learning techniques (i.e., nonparametric density estimation and Gaussian mixture models) to these measurements, two probabilistic models of harmonic injection of individual residential sites have been derived. Statistical probability distributions have been determined for the magnitude and phase of each harmonic order segmented in different power demand intervals. The developed models are validated on a test feeder by comparing harmonic voltages caused by the injection of the synthetically generated currents with those obtained from measurements. Both field measurement results and the detailed data defining the probabilistic harmonic current models are made public in an Open Science database repository.