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

Authors :
Fang, Luxin
Pengwah, Abu Bakr
Andrew, Lachlan L.H.
Razzaghi, Reza
Muñoz, Mario Andrés
Source :
International Journal of Electrical Power & Energy Systems. Jul2024, Vol. 158, pN.PAG-N.PAG. 1p.
Publication Year :
2024

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. • Estimating voltage sensitivity to current of low-voltage distribution network. • Estimation uses smart meter measurements only. • Transformer voltage is estimated simultaneously. • Approximating unknown phase angle and considering coupling effect on neutral line. • A fast Recursive-Grouping and Backtracking algorithm to find topology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01420615
Volume :
158
Database :
Academic Search Index
Journal :
International Journal of Electrical Power & Energy Systems
Publication Type :
Academic Journal
Accession number :
176865863
Full Text :
https://doi.org/10.1016/j.ijepes.2024.109949