A Complex-LASSO Approach for Localizing Forced Oscillations in Power Systems

Rajasekhar Anguluri, Nima Taghipourbazargani, Oliver Kosut, Lalitha Sankar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We study the problem of localizing multiple sources of forced oscillations (FOs) and estimating their characteristics, including frequency, phase, and amplitude, using noisy PMU data. We assume sparsity in the number of locations, and for each location, we model the input FO as a sum of a few unknown sinusoids. This allows us to obtain a sparse linear model in the frequency domain that relates measurements and the unknown input locations at frequencies of the unknown sinusoidal terms. We determine these frequencies by thresholding the empirical spectrum of the noisy data. Finally, we cast the location recovery problem as an ell_{1}-regularized least squares problem in the complex domain-i.e., complex-LASSO (linear shrinkage and selection operator). We numerically solve this optimization problem using the complex-valued coordinate descent method and show its efficiency on the IEEE 68-bus, 16 machine and WECC 179-bus, 29-machine systems.

Original languageEnglish (US)
Title of host publication2022 IEEE Power and Energy Society General Meeting, PESGM 2022
PublisherIEEE Computer Society
ISBN (Electronic)9781665408233
DOIs
StatePublished - 2022
Event2022 IEEE Power and Energy Society General Meeting, PESGM 2022 - Denver, United States
Duration: Jul 17 2022Jul 21 2022

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2022-July
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2022 IEEE Power and Energy Society General Meeting, PESGM 2022
Country/TerritoryUnited States
CityDenver
Period7/17/227/21/22

Keywords

  • complex-LASSO
  • Forced oscillations
  • PMU measurements
  • sampled data system
  • sparsity

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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