ESTIMATION OF THE ADMITTANCE MATRIX IN POWER SYSTEMS UNDER LAPLACIAN AND PHYSICAL CONSTRAINTS

Morad Halihal, Tirza Routtenberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Admittance matrix estimation in power networks enables faster control actions following emergency scenarios, energy-saving, and other economic and security advantages. In this paper, our goal is to estimate the network admittance matrix, i.e. to learn connectivity and edge weights in the graph representation, under physical and Laplacian constraints. We use the nonlinear AC power flow measurement model, which is based on Kirchhoff's and Ohm's laws, with power and voltage phasor measurements. In order to recover the complex-valued admittance matrix, we formulate the associated constrained maximum likelihood (CML) estimator as the solution of a constrained optimization problem with Laplacian and sparsity constraints. We develop an efficient solution using the associated alternating direction method of multipliers (ADMM) algorithm with an '1 relaxation. The ADMM algorithm is shown to outperform existing methods in the task of recovering the IEEE 14-bus test case.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5972-5976
Number of pages5
ISBN (Electronic)9781665405409
DOIs
StatePublished - 1 Jan 2022
Event47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
Duration: 23 May 202227 May 2022

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2022-May
ISSN (Print)1520-6149

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/TerritorySingapore
CityVirtual, Online
Period23/05/2227/05/22

Keywords

  • Admittance matrix estimation
  • alternating direction method of multipliers (ADMM)
  • graph learning
  • power system topology
  • topology identification

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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