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.
@article{arxiv.2105.10111,
title = {Simultaneous Robust State Estimation, Topology Error Processing, and Outage Detection for Unbalanced Distribution Systems},
author = {Zahra Soltani and Shanshan Ma and Mojdeh Khorsand and Vijay Vittal},
journal= {arXiv preprint arXiv:2105.10111},
year = {2021}
}