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A practical approach to optimising distribution transformer tap settings


Paoli, J and Brinkmann, B and Negnevitsky, M, A practical approach to optimising distribution transformer tap settings, Energies, 13, (18) Article 4889. ISSN 1996-1073 (2020) [Refereed Article]


Copyright Statement

Copyright 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (

DOI: doi:10.3390/en13184889


This paper proposes a method of determining the optimal tap settings for no-load distribution transformers with tap-changing capabilities that is practical to apply in real distribution networks. The risk of low voltage distribution networks violating voltage constraints is impacted by the increasing uptake of distributed energy resources and embedded generation. Some of this risk can be alleviated by suitably setting no-load transformer tap settings, however, modifying these taps requires customer outages and must be infrequent. Hence, loading over the entire year must be considered to account for seasonal variations when setting these taps optimally. These settings are determined using evolution strategy optimisation based on an average loading case. Monte Carlo simulations are used to calculate the probability that the terminal voltages on the distribution transformer secondary terminals violate the network voltage limits when the optimal set of taps for the average case is applied over a whole year. This algorithm was tested on several cases of a real distribution feeder of varying complexity, and produces a sufficiently-optimal set of taps without significant computation time.

Item Details

Item Type:Refereed Article
Keywords:no-load tap-changing transformers, optimisation, evolution strategy, distribution network utilisation, network planning
Research Division:Engineering
Research Group:Electrical engineering
Research Field:Electrical energy generation (incl. renewables, excl. photovoltaics)
Objective Division:Energy
Objective Group:Energy efficiency
Objective Field:Industrial energy efficiency
UTAS Author:Paoli, J (Mr Joshua Paoli)
UTAS Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:142982
Year Published:2020
Web of Science® Times Cited:1
Deposited By:Engineering
Deposited On:2021-02-18
Last Modified:2021-03-30
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