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Article | Open Access

Topology and admittance estimation: Precision limits and algorithms

Ning Zhang1, Yuxiao Liu1( ), Fangyuan Si2, Qingchun Hou1, Audun Botterud3, Chongqing Kang1
Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Laboratory of Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
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Abstract

Distribution grid topology and admittance information are essential for system planning, operation, and protection. In many distribution grids, missing or inaccurate topology and admittance data call for efficient estimation methods. However, measurement data may be insufficient or contaminated with large noise, which will fundamentally limit the estimation accuracy. This work explores the theoretical precision limits of the topology and admittance estimation (TAE) problem with different measurement devices, noise levels, and numbers of measurements. On this basis, we propose a conservative progressive self-adaptive (CPS) algorithm to estimate the topology and admittance. The results on IEEE 33 and 141-bus systems validate that the proposed CPS method can approach the theoretical precision limits under various measurement settings.

Keywords

data-drivenDistribution gridstopology estimationadmittance estimationNewton−Raphson method

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iEnergy
Volume 2 Issue 4,
December 2023
Pages 297-307
DOI: 10.23919/IEN.2023.0035
Cite this article:
Zhang N, Liu Y, Si F, et al. Topology and admittance estimation: Precision limits and algorithms. iEnergy, 2023, 2(4): 297-307. https://doi.org/10.23919/IEN.2023.0035

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Received: 10 July 2023
Revised: 23 September 2023
Accepted: 29 October 2023
Published: 30 November 2023
© The author(s) 2023.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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