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

TL;DR

This paper introduces a unified MIQP-based algorithm for real-time state estimation, topology error correction, and outage detection in unbalanced distribution systems, addressing measurement limitations and system nonlinearities.

Contribution

It develops a single MIQP framework that models unbalanced systems accurately and integrates multiple functions for improved reliability and efficiency.

Findings

Effective on real distribution feeder in Arizona

Handles measurement data issues and system nonlinearities

Simultaneously estimates state, detects outages, corrects topology

Abstract

This paper proposes an efficient algorithmic approach that overcomes the critical challenges in the real-time unbalanced distribution system state estimation, topology error processing, and outage identification simultaneously: (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 (3) the nonlinear nature of unbalanced distribution system power flow and measurement data . A single snap-shot mixed-integer quadratic programming (MIQP) optimization framework is proposed to cope with these challenges. This MIQP framework presents a more accurate unbalanced distribution system model, linearizes the nonlinear relationship between bus voltage and current injections, formulates the complicated mixed-phase switch operations, and executes the outage detection function via analytic constraints. The proposed model can be effectively solved by a general commercial MIP solver. The effectiveness of the proposed approach is verified on an actual distribution feeder in Arizona.