Enhancing power grid safety through Robust Fault Location research

New research at FRS increases the efficiency and reliability of detecting issues in power networks.  

by Guangxiao Zhang

Fault Location is the study of determining the precise fault point in overhead or cable power lines to enable quick and accurate repairs. Understanding where faults are is critical to keep complex networks, such as power grids or public utilities, resilient from disruption.

A team of researchers, led by FRS’s Prof. Gaoxi Xiao and Dr Guangxiao Zhang, et al., have developed new robust wide-area fault location methods. Their work specifically targets the challenge of ‘bad data’ – the manipulation of fault location results arising from sensor and communication failures, or deliberate cybersecurity threats.

In practical engineering terms, fault location methods widely rely on measurements from one or more ends of transmission lines, requiring substantial equipment and infrastructure to be implemented on each line. These methods may falter if measurements from one end are unavailable or compromised.

Now, the advent of advanced wide-area measurement and communication technologies has led to the proposal of wide-area fault location methods. The team's approach builds on this advancement by using data from strategically-placed phasor measurement units (PMUs) to accurately pinpoint fault locations across power grids.

This research’s novelty lies in its robust design, which effectively handles outliers in both measurements and network parameters, in contrast to existing studies that address only outliers in measurements. This advancement promises to enhance the safety and reliability of power grid operations, by providing a more resilient framework for identifying and locating faults.
 

G. Zhang, G. Xiao, X. Liu, Y. Xu and P. Wang, "A Robust Wide-Area Fault Location Method for Transmission Lines With Uncertainties in Measurements and Network Parameters," in IEEE Transactions on Power Delivery, vol. 39, no. 1, pp. 687-690, Feb. 2024, external pagedoi: 10.1109/TPWRD.2023.3343153.

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