A Practical Approach to Optimising Distribution Transformer Tap Settings

Joshua Paoli, Bernd Brinkmann and Michael Negnevitsky
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Joshua Paoli: School of Engineering, University of Tasmania, Hobart 7001, Australia
Bernd Brinkmann: TasNetworks, Lenah Valley 7008, Australia
Michael Negnevitsky: School of Engineering, University of Tasmania, Hobart 7001, Australia

Energies, 2020, vol. 13, issue 18, 1-16

Abstract: 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.

Keywords: no-load tap-changing transformers; optimisation; evolution strategy; distribution network utilisation; network planning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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