Urban distribution grid topology reconstruction via Lasso

Yizheng Liao, Yang Weng, Ram Rajagopal

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

44 Scopus citations


The growing integration of distributed energy resources (DERs) in urban areas raises various reliability issues. To ensure robust distribution grid operation, grid monitoring tools are needed, where the topology reconstruction serves as the first step. However, the topology reconstruction is hard in distribution grid. This is because 1) the branches are difficult and expensive to monitor since most of them are underground in urban areas; and 2) the assumption of radial topology in many studies is inappropriate for meshed urban grids. To address these drawbacks, we propose a new data-driven approach to reconstruct distribution grid topology by utilizing the newly available smart meter data. Specifically, a graphical model is built to model the probabilistic relationships among different voltage measurements. With proof, the topology reconstruction problem is formulated as a regularized linear regression problem (Lasso) to deal with meshed network structures. Simulation results show highly accurate estimation in IEEE standard distribution test systems with and without loops using real smart meter data.

Original languageEnglish (US)
Title of host publication2016 IEEE Power and Energy Society General Meeting, PESGM 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781509041688
StatePublished - Nov 10 2016
Externally publishedYes
Event2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States
Duration: Jul 17 2016Jul 21 2016

Publication series

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


Other2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Country/TerritoryUnited States

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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