Incipient Fault Location in Underground Distribution Networks Using Electromagnetic Time Reversal

Costa, Lucas Araujo da; Gazzana, Daniel S.; Leborgne, Roberto Chouhy; Thomas, Dave

doi:10.1109/eeeic/icpseurope49358.2020.9160622

Cited by 3 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The incipient faults are transient events that occur at random locations and are pre-emptive hidden faults before permanent faults occur. Incipient faults in the power distribution network usually occur in underground cables [5], [25], [26], transformer equipment [27], [28], distribution networks with high Distributed Energy Resources (DERS) penetration [29], and so on. There are many reasons for incipient faults, such as tree interference, animal contact and coil contact [14].…”

Section: A Faults In Power Distribution Systemsmentioning

confidence: 99%

Incipient Fault Detection in Power Distribution System: A Time–Frequency Embedded Deep-Learning-Based Approach

Luo

Cheng

et al. 2023

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

Incipient fault detection in power distribution systems is crucial to improve the reliability of the grid. However, the non-stationary nature and the inadequacy of the training dataset due to the self-recovery of the incipient fault signal, make the incipient fault detection in power distribution systems a great challenge. In this paper, we focus on incipient fault detection in power distribution systems and address the above challenges.In particular, we propose an ADaptive Time-Frequency Memory (AD-TFM) cell by embedding wavelet transform into the Long Short-Term Memory (LSTM), to extract features in time and frequency domain from the non-stationary incipient fault signals.We make scale parameters and translation parameters of wavelet transform learnable to adapt to the dynamic input signals.Based on the stacked AD-TFM cells, we design a recurrent neural network with ATtention mechanism, named AD-TFM-AT model, to detect incipient fault with multi-resolution and multi-dimension analysis. In addition, we propose two data augmentation methods, namely phase switching and temporal sliding, to effectively enlarge the training datasets. Experimental results on two open datasets show that our proposed AD-TFM-AT model and data augmentation methods achieve state-of-theart (SOTA) performance of incipient fault detection in power distribution system. We also disclose one used dataset logged at State Grid Corporation of China to facilitate future research.

show abstract

Section: A Faults In Power Distribution Systemsmentioning

confidence: 99%

Incipient Fault Detection in Power Distribution System: A Time–Frequency Embedded Deep-Learning-Based Approach

Luo

Cheng

et al. 2023

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

show abstract

Automated tiered Detection of Cyber-Attacks in Operational Distribution Networks

Brintha,

Balaji,

Teja

et al. 2024

2024 8th International Conference on Inventive Systems and Control (ICISC)

View full text Add to dashboard Cite

Synchronous Waveform Measurements to Locate Transient Events and Incipient Faults in Power Distribution Networks

Izadi

Mohsenian‐Rad

2021

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

A new method is proposed to identify the location of transient events, including incipient faults, in power distribution systems, by using synchronized measurements from an emerging class of sensors, called waveform measurement units (WMUs). WMUs capture the voltage and current waveforms in time domain. The proposed method consists of three steps. The first step is to characterize the oscillatory modes of the transient components of all the captured synchronized voltage and current waveforms from all WMUs, by conducting a multi-signal modal analysis. The second step is to construct a circuit model for the underlying distribution feeder at the identified dominant mode(s) of the transient event. The final step is to identify the location of the transient event with the means of a method that involves certain forward and backward analyses of the constructed circuit model. The proposed method requires installing as few as only two WMUs. It can also utilize several synchronized waveform measurements when several WMUs are available. The performance of the proposed method is assessed on the IEEE 33-bus test system; for different cases of transient events, such as sub-cycle incipient faults, multi-cycle incipient faults, permanent faults, as well as benign yet informative events such as capacitor bank switching. Both the accuracy and the robustness of the proposed method are verified. The analysis and results in this paper provide new insights on possible applications of synchronized WMU measurements; while they also address a highly challenging problem in power distribution networks.

show abstract

Incipient Fault Location in Underground Distribution Networks Using Electromagnetic Time Reversal

Cited by 3 publications

References 15 publications

Incipient Fault Detection in Power Distribution System: A Time–Frequency Embedded Deep-Learning-Based Approach

Incipient Fault Detection in Power Distribution System: A Time–Frequency Embedded Deep-Learning-Based Approach

Automated tiered Detection of Cyber-Attacks in Operational Distribution Networks

Synchronous Waveform Measurements to Locate Transient Events and Incipient Faults in Power Distribution Networks

Contact Info

Product

Resources

About