A data-driven approach for topology correction in low voltage distribution networks with PVs
Dong Liu, Sander Timmerman, Yu Xiang, Ensieh Hosseini, Peter Palensky, and Pedro P. Vergara

TL;DR
This paper proposes a data-driven method to identify and correct outdated low-voltage distribution network topologies affected by distributed energy resources and limited smart meter data.
Contribution
It introduces a novel approach for real-time topology correction in low-voltage networks considering uncertainties and data limitations.
Findings
Addresses topology inaccuracies due to DERs and outdated data.
Develops a method suitable for real-time topology updating.
Handles limited and privacy-sensitive smart meter datasets.
Abstract
Most existing phase balancing and topology reconfiguration problems are formulated as mixed-integer optimization problems that depend on network topologies~\cite{10098964,11017695,10571996}. However, these topologies are often inaccurate and outdated for distribution system operators~(DSOs) due to missing recordings, topology maintenance and reconfiguration, such as congestion management ~\cite{vanin2024phase}. Thus, the topology of the low-voltage distribution network (LVDN) needs to be checked and corrected when it is outdated. The increasing uncertainty of distributed energy resources (DERs), including household photovoltaic (PV), heating pumps, etc., impacts the frequency of topology reconfiguration and challenges the correction of the low-voltage distribution network topology~\cite{10026490, 10347462, 10475702}. Moreover, the available smart meter (SM) datasets are often limited…
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