A Self-Healing and Resilience Enhancement Strategy for Single-Phase Grounding Faults in Distribution Networks Based on Zonal Hierarchical Load Shedding

The distribution network, serving as a critical component of the power grid, is responsible for delivering electricity from the main grid to end-users in the “last mile”. Its secure and stable operation is essential for constructing a modern power system and driving socio-economic development. However, the current distribution network faces three major resilience challenges: exponential growth in the topological complexity of distributed devices, inadequate adaptive reconfiguration capability of the grid structure, and imperfect mechanisms for rapid fault isolation and power restoration. These challenges result in an N-1 pass rate below 78%, posing significant threats to the secure and stable operation of the power grid and negatively impacting users' power experience. To address these resilience bottlenecks, this study focuses on single-phase grounding faults, which constitute the majority of distribution network incidents, and proposes a self-healing strategy for distribution line single-phase grounding faults based on zonal hierarchical load shedding, leveraging the existing main grid sequential control line selection mode. By integrating system data and conducting comprehensive analysis, along with technologies such as categorized hierarchical trial switch, intelligent single-phase grounding fault diagnosis, and fully automated load transfer, this approach significantly mitigates the impact of power outages, reduces users' perception of power loss, and enhances the power supply resilience index. Currently, this method has been fully implemented in Wuxi City and has undergone resilience verification under typhoon disaster scenarios.

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Publication Details

Published
2025-04-15
DOI
https://doi.org/10.1109/acpee64358.2025.11041525
Primary Topic
Power Systems Fault Detection
Type
article
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article

A Self-Healing and Resilience Enhancement Strategy for Single-Phase Grounding Faults in Distribution Networks Based on Zonal Hierarchical Load Shedding

Yuwei Sun, Rongjin Cai, Li Chen, Xiaodong Liu et al.
Power Systems Fault Detection
article

A Self-Healing and Resilience Enhancement Strategy for Single-Phase Grounding Faults in Distribution Networks Based on Zonal Hierarchical Load Shedding

Yuwei Sun, Rongjin Cai, Li Chen, Xiaodong Liu, Xiaofeng Zhou, Yuan Gao
article en

Abstract

The distribution network, serving as a critical component of the power grid, is responsible for delivering electricity from the main grid to end-users in the “last mile”. Its secure and stable operation is essential for constructing a modern power system and driving socio-economic development. However, the current distribution network faces three major resilience challenges: exponential growth in the topological complexity of distributed devices, inadequate adaptive reconfiguration capability of the grid structure, and imperfect mechanisms for rapid fault isolation and power restoration. These challenges result in an N-1 pass rate below 78%, posing significant threats to the secure and stable operation of the power grid and negatively impacting users' power experience. To address these resilience bottlenecks, this study focuses on single-phase grounding faults, which constitute the majority of distribution network incidents, and proposes a self-healing strategy for distribution line single-phase grounding faults based on zonal hierarchical load shedding, leveraging the existing main grid sequential control line selection mode. By integrating system data and conducting comprehensive analysis, along with technologies such as categorized hierarchical trial switch, intelligent single-phase grounding fault diagnosis, and fully automated load transfer, this approach significantly mitigates the impact of power outages, reduces users' perception of power loss, and enhances the power supply resilience index. Currently, this method has been fully implemented in Wuxi City and has undergone resilience verification under typhoon disaster scenarios.

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Power Systems Fault Detection
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