Journal Article

FZJ-2018-05778

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Inferring power-grid topology in the face of uncertainties

Basiri, F.FZJ* ; Casadiego, J. ; Timme, M. ; Witthaut, D. (Corresponding author)FZJ*

2018
Inst. Woodbury, NY

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Please use a persistent id in citations: http://hdl.handle.net/2128/19825  doi:10.1103/PhysRevE.98.012305

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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Contributing Institute(s):

1. Systemforschung und Technologische Entwicklung (IEK-STE)

Research Program(s):

1. 153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153) (POF3-153)
2. CoNDyNet - Kollektive Nichtlineare Dynamik Komplexer Stromnetze (PIK_082017) (PIK_082017)
3. VH-NG-1025 - Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" (VH-NG-1025_20112014) (VH-NG-1025_20112014)

Appears in the scientific report 2018

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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