Three-phase voltage sensitivity estimation and its application to topology identification in low-voltage distribution networks

Abstract

This paper aims to estimate the three-phase voltage sensitivity matrix and the network topology of a low-voltage distribution network from smart meter data, which measures voltage magnitude, current magnitude, and power factor with a lead/lag indicator. The targeted networks are three-phase networks with single-phase loads. Understanding network sensitivity and topology is crucial for fault detection, unmetered load identification, and addressing Dynamic Operating Envelope problems. The problem is formulated as a constrained optimization problem to estimate both the three-phase voltage sensitivity and the low-voltage transformer voltage. The estimated voltage sensitivity is used to further identify the network topology, by implementing an enhanced Recursive-Grouping and Backtracking algorithm, as well as a candidate topology selection technique. The proposed method is tested on the 55-node European feeder and several synthetic networks. Compared to the state-of-the-art, the results show a four-fold improvement in the accuracy of voltage sensitivity estimation and substantially fewer mistakes in the topology estimates. The result underscores the efficacy of a three-phase network model and voltage angle approximation in enhancing estimation accuracy.