This title appears in the Scientific Report :
2018
Please use the identifier:
http://dx.doi.org/10.1103/PhysRevE.98.012305 in citations.
Please use the identifier: http://hdl.handle.net/2128/19825 in citations.
Inferring power-grid topology in the face of uncertainties
Inferring power-grid topology in the face of uncertainties
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, an...
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Personal Name(s): | Basiri, Farnaz |
---|---|
Casadiego, Jose / Timme, Marc / Witthaut, Dirk (Corresponding author) | |
Contributing Institute: |
Systemforschung und Technologische Entwicklung; IEK-STE |
Published in: | Physical Review E Physical review / E, 98 98 (2018 2018) 1 1, S. 012305 012305 |
Imprint: |
Woodbury, NY
Inst.
2018
2018-07-12 2018-07-01 |
DOI: |
10.1103/PhysRevE.98.012305 |
PubMed ID: |
30110818 |
Document Type: |
Journal Article |
Research Program: |
Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" Kollektive Nichtlineare Dynamik Komplexer Stromnetze Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/19825 in citations.
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. |