Joint Topology Identification and State Estimation in Unobservable Distribution Grids

Karimi, Hazhar Sufi; Natarajan, Balasubramaniam

doi:10.1109/tsg.2021.3102179

Joint Topology Identification and State Estimation in Unobservable Distribution Grids

Journal Article · Tue Aug 03 00:00:00 EDT 2021 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/tsg.2021.3102179· OSTI ID:1907350

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Kansas State Univ., Manhattan, KS (United States); Kansas State University
Kansas State Univ., Manhattan, KS (United States)

Many distribution system operations (e.g., state estimation, control, fault detection/localization) rely on the assumption that the underlying topology is accurately defined. In general, topology identification is a challenging problem in distribution systems as these systems are unobservable with a very limited number of available measurements. In this paper, we tackle this problem by designing a compressive sensing framework that jointly estimates the systems states and network topology via an integrated mixed integer nonlinear program (MINLP) formulation. Here, two reformulations of the original MINLP problems are investigated. Firstly, in order to remove the nonlinearity in the MINLP formulation, a mixed integer linear programming (MILP) problem that employs auxiliary variables is derived. Furthermore, to achieve a faster solution, convex relaxation of the original formulation is derived. Finally, using a Markovian model for topology changes, prior information about system topology is used to improve topology identification particularly when a limited amount of measurements is available. Simulation results on IEEE 37-bus test feeder and IEEE 123-bus test feeder illustrate the efficiency and scalability of the proposed approaches from both state estimation and topology identification point of view (even with 30% of available data).

View Accepted Manuscript (DOE)

Research Organization:: Kansas State Univ., Manhattan, KS (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

Grant/Contract Number:: EE0008767

OSTI ID:: 1907350

Report Number(s):: DOE-KSU-8767; TSG-01828-2020

Journal Information:: IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 6 Vol. 12; ISSN 1949-3053

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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42 ENGINEERING
compressive sensing
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Joint Topology Identification and State Estimation in Unobservable Distribution Grids

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