Simultaneous Robust State Estimation, Topology Error Processing, and Outage Detection for Unbalanced Distribution Systems

Zahra Soltani, Shanshan Ma, Mojdeh Khorsand, Vijay Vittal

Research output: Contribution to journalArticlepeer-review


This paper proposes an efficient algorithmic approach that overcomes the critical challenges in real-time unbalanced distribution system state estimation, topology error processing, and outage identification simultaneously. These challenges include (1) limited locations of measurement devices and unsynchronized measurement data as well as missing and bad data, (2) complicated mixed-phase switch actions and mutual impedances and shunt admittances, and (3) the nonlinear nature of unbalanced distribution system power flow with distributed energy resources (DERs). A single snap-shot mixed-integer quadratic programming (MIQP) optimization framework is proposed to cope with these challenges, which simultaneously identifies real-time network topology, estimates system state, and detects the outages via analytical constraints. An AC optimal power flow (ACOPF) approach is proposed to accurately model unbalanced distribution systems. In the proposed MIQP formulation, nonlinearities due to the complicated mixed-phase switch operations and the ACOPF approach are linearized. The effectiveness of the proposed approach is verified on an actual distribution feeder in Arizona. The results illustrate that the proposed model is robust, accurate, and computationally efficient for implementation in a distribution management system (DMS).

Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalIEEE Transactions on Power Systems
StateAccepted/In press - 2022


  • AC optimal power flow
  • bad data
  • Current measurement
  • distribution system state estimation
  • Load flow
  • missing data
  • Network topology
  • outage detection
  • Real-time systems
  • State estimation
  • Switches
  • Topology
  • Topology error processing
  • unbalanced distribution systems
  • unsynchronized measurement data

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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