{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/on-identification-of-distribution-grids","title":"On Identification of Distribution Grids","arxiv_id":"1711.01526","date":"2017-11-05","proceeding":null,"authors":["Omid Ardakanian","Vincent W. S. Wong","Roel Dobbe","Steven H. Low","Alexandra von Meier","Claire Tomlin","Ye Yuan"],"abstract":"Large-scale integration of distributed energy resources into residential\ndistribution feeders necessitates careful control of their operation through\npower flow analysis. While the knowledge of the distribution system model is\ncrucial for this type of analysis, it is often unavailable or outdated. The\nrecent introduction of synchrophasor technology in low-voltage distribution\ngrids has created an unprecedented opportunity to learn this model from\nhigh-precision, time-synchronized measurements of voltage and current phasors\nat various locations. This paper focuses on joint estimation of model\nparameters (admittance values) and operational structure of a poly-phase\ndistribution network from the available telemetry data via the lasso, a method\nfor regression shrinkage and selection. We propose tractable convex programs\ncapable of tackling the low rank structure of the distribution system and\ndevelop an online algorithm for early detection and localization of critical\nevents that induce a change in the admittance matrix. The efficacy of these\ntechniques is corroborated through power flow studies on four three-phase\nradial distribution systems serving real household demands.","url_abs":"http://arxiv.org/abs/1711.01526v1","url_pdf":"http://arxiv.org/pdf/1711.01526v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"on-identification-of-distribution-grids","repo_url":"https://github.com/sustainable-computing/Distribution-Grid-Identification","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}