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Grid Topology Identification using Electricity Prices

Authors
  • Kekatos, Vassilis
  • Giannakis, Georgios B.
  • Baldick, Ross
Type
Preprint
Publication Date
Feb 13, 2014
Submission Date
Dec 02, 2013
Identifiers
arXiv ID: 1312.0516
Source
arXiv
License
Yellow
External links

Abstract

The potential of recovering the topology of a grid using solely publicly available market data is explored here. In contemporary whole-sale electricity markets, real-time prices are typically determined by solving the network-constrained economic dispatch problem. Under a linear DC model, locational marginal prices (LMPs) correspond to the Lagrange multipliers of the linear program involved. The interesting observation here is that the matrix of spatiotemporally varying LMPs exhibits the following property: Once premultiplied by the weighted grid Laplacian, it yields a low-rank and sparse matrix. Leveraging this rich structure, a regularized maximum likelihood estimator (MLE) is developed to recover the grid Laplacian from the LMPs. The convex optimization problem formulated includes low rank- and sparsity-promoting regularizers, and it is solved using a scalable algorithm. Numerical tests on prices generated for the IEEE 14-bus benchmark provide encouraging topology recovery results.

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