Online estimation of power system distribution factors - A sparse representation approach

This paper proposes a method to compute linear sensitivity distribution factors (DFs) in near real-time without relying on a power flow model of the system. Instead, the proposed method relies on the solution of an underdetermined system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. In particular, we exploit a sparse representation (i.e., one in which many elements are zero) of the desired DFs obtained via a linear transformation, and cast the estimation problem as an io-norm minimization. As we illustrate through examples, the proposed approach is able to provide accurate DF estimates with fewer sets of synchronized measurements than earlier approaches that rely on the solution of an overdetermined system of equations via the least-squares errors method.