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  Inferring power-grid topology in the face of uncertainties

Basiri, F., Casadiego Bastidas, J. L., Timme, M., & Witthaut, D. (2018). Inferring power-grid topology in the face of uncertainties. Physical Review E, 98(1): 012305. doi:10.1103/PhysRevE.98.012305.

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 Creators:
Basiri, Farnaz, Author
Casadiego Bastidas, José Luis1, Author              
Timme, Marc1, Author              
Witthaut, Dirk, Author
Affiliations:
1Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063295              

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 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.

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Language(s): eng - English
 Dates: 2018-07-122018-07
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1103/PhysRevE.98.012305
 Degree: -

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Title: Physical Review E
Source Genre: Journal
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Publ. Info: Melville, NY : American Physical Society
Pages: 10 Volume / Issue: 98 (1) Sequence Number: 012305 Start / End Page: - Identifier: ISSN: 1539-3755
CoNE: https://pure.mpg.de/cone/journals/resource/954925225012