Grid Topology Estimation in Electrical Markets via Diagonally Dominant Laplacian

Estimation of topology of the power grid from electrical markets has been a point of interest of the industry traders. Under a DC model, methods [1], [2] try to recover the grid Laplacian though locational marginal prices (LMPs) exist. However they give incompatible grid Laplacian after the full recovery, leaving positive off diagonal entries. This paper discusses a new model for grid topology estimation, which involves the key property of diagonal dominance to guarantee a compatible full recovery of grid topology. We develop alternating direction method of multipliers (ADMM) algorithm for the new model which is much more scalable than existing algorithms aiming to solve the same problem thanks to the newly introduced sum-log-diagonal term. Numerical experiments indicate that our method is highly scalable to the number of nodes and/or to the number of time steps of the data while giving higher quality solution.