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• W2989455840 abstract "To perform any meaningful optimization task, distribution grid operators need to know the topology of their grids. Although power grid topology identification and verification has been recently studied, discovering instantaneous interplay among subsets of buses, also known as higher-order interactions in recent literature, has not yet been addressed. The system operator can benefit from having this knowledge when re-configuring the grid in real time, to minimize power losses, balance loads, alleviate faults, or for scheduled maintenance. Establishing a connection between the celebrated exact distribution flow equations and the so-called self-driven graph Volterra model, this paper puts forth a nonlinear topology identification algorithm, that is able to reveal both the edge connections as well as their higher-order interactions. Preliminary numerical tests using real data on a 47-bus distribution grid showcase the merits of the proposed scheme relative to existing alternatives." @default.
• W2989455840 created "2019-11-22" @default.
• W2989455840 creator A5015683686 @default.
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• W2989455840 date "2019-11-08" @default.
• W2989455840 modified "2023-10-18" @default.
• W2989455840 title "Learning Connectivity and Higher-order Interactions in Radial Distribution Grids" @default.
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• W2989455840 doi "https://doi.org/10.48550/arxiv.1911.03072" @default.
• W2989455840 hasPublicationYear "2019" @default.
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