Summary

Aged electricity substations with non-intelligent, non-IEC61850 devices are still in operation and in some cases financial and resource constraints may prevent their upgrade. The lifespan of these assets continues to be extended, while maintenance spending has remained flat or decreased, even as public expectations for network reliability continue to rise, Moreover, these substations are predominantly in remote/rural areas, low capacity, low utilisation but high in maintenance costs to operate the network reliably.

This paper examines the use of available Supervisory, Control and Data Acquisition

(SCADA)/operational data, maintenance data, and modelled fault level information to optimise circuit breaker maintenance, in particular oil circuit breakers, of these legacy substations equipped with electro-mechanical, analogue, or non-integrated digital relays. SQL-driven interrogation of relational databases, followed by data processing through an algorithm developed using R, enables scalable and efficient network-wide analysis.

The analysed information provides the following:

1. circuit breaker timing condition monitoring trends, not absolute circuit breaker timing values, and 2. determination of post fault maintenance activity triggers by identifying genuine circuit breaker fault operations.

The above information is used to extend maintenance interval, identify and perform targeted maintenance where it is genuinely required thereby reducing maintenance cost while maintaining network reliability because of failures due to lack of maintenance.

Additional informations

Publication type Session Materials
Reference B3_10344_2026
Publication year
Publisher CIGRE
Country Australia
Study committees
File size 4 MB
Price for non member 30 €
Price for member 30 €

Authors

KHOR Jonathan - Energy Queensland, Australia; NARANPANAWE Lakshitha - Energy Queensland, Australia

Keywords

Substation SCADA, Circuit Breaker, Network Reliability

Application of Substation SCADA Data for Circuit Breaker Maintenance Optimisation and Network Reliability