Estimation of distribution grid line parameters using smart meter data with missing measurements

Grid models, including line impedances, are crucial for the active management and operation of the distribution grid (DG). This paper introduces a novel approach for estimating DG line parameters using available voltage magnitude and node powers from smart meters (SMs), specifically addressing scenarios with missing measurements. We propose an expectation–maximization (EM) based approach and validate the results on an IEEE 37-node network, achieving accurate estimates for line parameters, voltage magnitude, and active/reactive power at nodes. The method is tested with varying levels of missing measurements and noise. Two cases of missing measurements are considered: random and specific node-based. The latter case is used to infer the optimal placement of measurement devices. Additionally, the proposed method is validated on simulated data and real-world consumer loads, consistently providing accurate results.