hide
Free keywords:
-
Abstract:
We develop methods to efficiently reconstruct the topology and line parameters of a power grid from the
measurement of nodal variables. We propose two compressed sensing algorithms that minimize the amount of
necessary measurement resources by exploiting network sparsity, symmetry of connections, and potential prior
knowledge about the connectivity. The algorithms are reciprocal to established state estimation methods, where
nodal variables are estimated from few measurements given the network structure. Hence, they enable an advanced
grid monitoring where both state and structure of a grid are subject to uncertainties or missing information.
