Topology Identification and Line Parameter Estimation for Non-PMU Distribution Network: A Numerical Method

Jiawei Zhang, Yi Wang, Yang Weng, Ning Zhang

Research output: Contribution to journalArticlepeer-review

105 Scopus citations


The energy management system becomes increasingly indispensable with the extensive penetration of new players in the distribution networks, such as renewable energy, storage, and controllable load. Also, the operation optimization of the active distribution system requires information on operation state monitoring. Smart measuring equipment enables the topology identification and branch line parameters estimation from a data-driven perspective. Nevertheless, many current methods require the nodal voltage angles measured by phasor measurement units (PMUs), which might be unrealistic for conventional distribution networks. This paper proposes a numerical method to identify the topology and estimate line parameters without the information of voltage angles. We propose a two-step framework: the first step applies a data-driven regression method to provide a preliminary estimation on the topology and line parameter; the second step utilizes a joint data-and-model-driven method, i.e., a specialized Newton-Raphson iteration and power flow equations, to calculate the line parameter, recover voltage angle and further correct the topology. We test the method on IEEE 33 and 123-bus looped networks with load data from 1000 users in Ireland. The results demonstrate that the proposed method can provide an accurate estimation of the topology and line parameters based on limited samples of measurement without voltage angles.

Original languageEnglish (US)
Article number9027950
Pages (from-to)4440-4453
Number of pages14
JournalIEEE Transactions on Smart Grid
Issue number5
StatePublished - Sep 2020


  • Topology identification
  • data-driven
  • distribution network
  • smart meter
  • state estimation

ASJC Scopus subject areas

  • Computer Science(all)


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