Joint Estimation of Operational Topology and Outages for Unbalanced Power Distribution Systems

TL;DR

This paper introduces a MILP-based method for jointly estimating the operational topology and outages in unbalanced power distribution systems using measurements and load data, validated on large test systems.

Contribution

It proposes a novel mixed-integer linear programming approach that simultaneously estimates topology and outages in unbalanced systems, improving operational awareness.

Findings

Performs well even with high measurement errors

Accurately estimates topology in large test systems

Effective under both outage and normal conditions

Abstract

An electric power distribution system is operated in several distinct radial topologies by opening and closing of system's sectionalizing and tie switches. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). This paper presents a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. Specifically, a minimum weighted least absolute value estimator is proposed that uses the line flow measurements, historical/forecasted load data, and ping measurements and solves a mixed-integer linear program (MILP) to estimate the operational topology and any outaged sections simultaneously. We thoroughly validate the accuracy of the proposed approach using IEEE 123-bus and a 1069-bus three-phase multi-feeder test system with the help of numerous simulations. It is observed that the approach performs well even at high percentages of measurement errors.