A Staged Event Source Location Identification Scheme in Power Distribution Networks Under Extremely Low Observability

Recent advancements in synchrophasor measurement technologies have introduced an unprecedented level of visibility in power distribution networks (PDNs), providing a high-quality data foundation for the accurate perception of event source locations. However, the high cost and deployment expense pose a significant challenge in balancing system observability and event source location identification (ESLI) accuracy. In this paper, we propose a staged ESLI scheme based on voltage measurement deviation (VMD), which can achieve high-precision ESLI and event current calculations under extremely low-observability conditions, where the measurement devices are deployed only at the head substation and terminal buses. By setting an unknown event injection current and traversing each bus along the target feeder to derive the terminal bus voltage and its outgoing current, an ESLI model based on virtual event current injection (VCI) is constructed, which not only assists in the ESLI task but also confers the solving capability of the event current. Leveraging the event current calculation ability of the ESLI model, a VMD-based staged ESLI algorithm is developed, achieving an ordered and accurate search for the exact location of the event source in a goal-oriented manner. The effectiveness of the developed ESLI algorithm is evaluated on the IEEE 33-bus test system. Experimental results demonstrate that our VMD achieves high-precision ESLI and event current solving in PDNs under extremely low observability, significantly outperforming the state-of-the-art ESLI methods.

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Publication Details

Journal
Sensors
Published
2025-08-20
DOI
https://doi.org/10.3390/s25165169
Citations
1
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.73
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article

A Staged Event Source Location Identification Scheme in Power Distribution Networks Under Extremely Low Observability

Fei Mei, Jianyong Zheng, Xi Zhang
1 citations
Sensors
Power System Optimization and Stability
0.73
article

A Staged Event Source Location Identification Scheme in Power Distribution Networks Under Extremely Low Observability

Fei Mei, Jianyong Zheng, Xi Zhang
article en
1 citations

Abstract

Recent advancements in synchrophasor measurement technologies have introduced an unprecedented level of visibility in power distribution networks (PDNs), providing a high-quality data foundation for the accurate perception of event source locations. However, the high cost and deployment expense pose a significant challenge in balancing system observability and event source location identification (ESLI) accuracy. In this paper, we propose a staged ESLI scheme based on voltage measurement deviation (VMD), which can achieve high-precision ESLI and event current calculations under extremely low-observability conditions, where the measurement devices are deployed only at the head substation and terminal buses. By setting an unknown event injection current and traversing each bus along the target feeder to derive the terminal bus voltage and its outgoing current, an ESLI model based on virtual event current injection (VCI) is constructed, which not only assists in the ESLI task but also confers the solving capability of the event current. Leveraging the event current calculation ability of the ESLI model, a VMD-based staged ESLI algorithm is developed, achieving an ordered and accurate search for the exact location of the event source in a goal-oriented manner. The effectiveness of the developed ESLI algorithm is evaluated on the IEEE 33-bus test system. Experimental results demonstrate that our VMD achieves high-precision ESLI and event current solving in PDNs under extremely low observability, significantly outperforming the state-of-the-art ESLI methods.

SensorsVol. 25(16)
Hohai University (CN), Southeast University (CN)
Openalex Percentile: Top 24%
Power System Optimization and Stability
0.73
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A Staged Event Source Location Identification Scheme in Power Distribution Networks Under Extremely Low Observability — Fei Mei, Jianyong Zheng, et al. · Sensors (2025) | TGRS Research Map | TGRS