Urban distribution grid line outage identification

Yizheng Liao, Yang Weng, Chin Woo Tan, Ram Rajagopal

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

8 Scopus citations

Abstract

The growing integration of distributed energy resources (DERs) in urban distribution grids raises various reliability issues due to complex uncertainties. With the large-scale penetration of DERs, traditional outage detection methods, which rely on customers making phone calls and smart meters' 'last gasp' signals, will have limited performance because 1) the renewable generators can supply powers after line outages, and 2) many urban grids are mesh and line outages do not affect power supply. To address these drawbacks, we propose a new data-driven outage monitoring approach based on the stochastic time series analysis with the newly available smart meter data utilized. Specifically, based on the power flow analysis, we prove that the statistical dependency of time-series voltage measurements has significant changes after line outages. Hence, we use the optimal change point detection theory to detect and localize line outages. As the existing change point detection methods require the post-outage voltage distribution, which is unknown in power systems, we propose a maximum likelihood method to learn the distribution parameters from the historical data. The proposed outage detection using estimated parameters also achieves the optimal performance. Simulation results show highly accurate outage identification in IEEE standard distribution test systems with and without DERs using real smart meter data.

Original languageEnglish (US)
Title of host publication2016 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509019700
DOIs
StatePublished - Dec 1 2016
Externally publishedYes
Event2016 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2016 - Beijing, China
Duration: Oct 16 2016Oct 20 2016

Other

Other2016 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2016
CountryChina
CityBeijing
Period10/16/1610/20/16

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Statistics and Probability

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    Liao, Y., Weng, Y., Tan, C. W., & Rajagopal, R. (2016). Urban distribution grid line outage identification. In 2016 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2016 - Proceedings [7764218] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PMAPS.2016.7764218