Distribution Grid Modeling Using Smart Meter Data

The knowledge of distribution grid models, including topologies and line impedances, is essential for monitoring, control protection. However, such information often unavailable, incomplete or outdated. increasing deployment smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes two-stage framework modeling using SM data. In the first stage, network topology identified by reconstructing weighted Laplacian matrix networks. second least absolute deviations (LAD) regression model developed estimating impedance single branch based on nonlinear (inverse) power flow model, wherein conductor library leveraged narrow down solution space. LAD originally mixed-integer program whose continuous relaxation still non-convex. Thus, we specially address its convex discuss exactness. modified then embedded within bottom-up sweep algorithm achieve identification across in branch-wise manner. Numerical results IEEE 13-bus, 37-bus 69-bus test feeders validate effectiveness proposed methods.