On Identification of Distribution Grids
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Abstract (arXiv)
Large-scale integration of distributed energy resources into residential distribution feeders necessitates careful control of their operation through power flow analysis. While the knowledge of the distribution system model is crucial for this type of analysis, it is often unavailable or outdated. The recent introduction of synchrophasor technology in low-voltage distribution grids has created an unprecedented opportunity to learn this model from high-precision, time-synchronized measurements of voltage and current phasors at various locations. This paper focuses on joint estimation of model parameters (admittance values) and operational structure of a poly-phase distribution network from the available telemetry data via the lasso, a method for regression shrinkage and selection. We propose tractable convex programs capable of tackling the low rank structure of the distribution system and develop an online algorithm for early detection and localization of critical events that induce a change in the admittance matrix. The efficacy of these techniques is corroborated through power flow studies on four three-phase radial distribution systems serving real household demands.
Key facts. Cited by 6 papers in the map (data through 13 Oct 2026). First posted on arXiv 5 Nov 2017.
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Citing papers per year: 2021: 3; 2022: 2; 2023: 0; 2024: 0; 2025: 1.
6 papers.
- 2022Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systemscited by 12
- 2022Learning Distribution Grid Topologies: A Tutorialcited by 3
- 2021Estimate Three-Phase Distribution Line Parameters With Physics-Informed Graphical Learning Methodcited by 1
- 2025SODAs: Sparse Optimization for the Discovery of Differential and Algebraic Equationscited by 1
- 2021Bayesian Error-in-Variables Models for the Identification of Power Networkscited by 0
- 2021Data-driven Modeling for Distribution Grids Under Partial Observabilitycited by 0
- 2025SODAs: Sparse Optimization for the Discovery of Differential and Algebraic Equations8 Mar 2025
- 2022Learning Distribution Grid Topologies: A Tutorial22 Jun 2022
- 2022Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems11 Feb 2022
- 2021Data-driven Modeling for Distribution Grids Under Partial Observability18 Aug 2021
- 2021Bayesian Error-in-Variables Models for the Identification of Power Networks9 Jul 2021
- 2021Estimate Three-Phase Distribution Line Parameters With Physics-Informed Graphical Learning Method17 Feb 2021