A Multi-Stage Resilience Enhancement Method for Distribution Systems Considering Faulty Remote-Controlled Switches and Crew Dispatch

Extreme events threaten distribution network security. When remote-controlled switches (RCSs) lose remote operability during extreme events while remaining manually operable, faulted areas may no longer be isolated through remote switching alone. This paper proposes a multi-stage resilience enhancement method that coordinates RCSs and switch operation crews under RCS fault conditions. A four-stage framework is established, comprising pre-event prevention, degradation, fault isolation, and service restoration. Normal RCSs can be remotely opened to shrink the faulted zone during isolation, while faulty RCSs remain frozen and can change their switching states only through on-site crew intervention during restoration. A unified operation constraint is formulated for the isolation stage, and a crew-assisted switching constraint links crew presence at faulty-RCS locations to their switching operability during restoration. The problem is cast as a scenario-based mixed-integer linear program minimizing expected weighted load shedding across all post-event stages. Case studies on the modified IEEE 33-bus system demonstrate the effectiveness of the proposed method under different RCS availability conditions. Under the same line-fault configuration, loss of RCS remote operability increases cumulative weighted load shedding by 28.09% and delays complete load restoration by one time interval. The reported four-scenario computation required approximately 7128 s.

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Publication Details

Journal
Energies
Published
2026-09-20
DOI
https://doi.org/10.3390/en19184450
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

A Multi-Stage Resilience Enhancement Method for Distribution Systems Considering Faulty Remote-Controlled Switches and Crew Dispatch

Xinyun Lu, Jiancun Liu, Shuonan Hou, Zhengwei Shen et al.
Energies
Optimal Power Flow Distribution
article

A Multi-Stage Resilience Enhancement Method for Distribution Systems Considering Faulty Remote-Controlled Switches and Crew Dispatch

Xinyun Lu, Jiancun Liu, Shuonan Hou, Zhengwei Shen, Xiaopei Zhang
article en

Abstract

Extreme events threaten distribution network security. When remote-controlled switches (RCSs) lose remote operability during extreme events while remaining manually operable, faulted areas may no longer be isolated through remote switching alone. This paper proposes a multi-stage resilience enhancement method that coordinates RCSs and switch operation crews under RCS fault conditions. A four-stage framework is established, comprising pre-event prevention, degradation, fault isolation, and service restoration. Normal RCSs can be remotely opened to shrink the faulted zone during isolation, while faulty RCSs remain frozen and can change their switching states only through on-site crew intervention during restoration. A unified operation constraint is formulated for the isolation stage, and a crew-assisted switching constraint links crew presence at faulty-RCS locations to their switching operability during restoration. The problem is cast as a scenario-based mixed-integer linear program minimizing expected weighted load shedding across all post-event stages. Case studies on the modified IEEE 33-bus system demonstrate the effectiveness of the proposed method under different RCS availability conditions. Under the same line-fault configuration, loss of RCS remote operability increases cumulative weighted load shedding by 28.09% and delays complete load restoration by one time interval. The reported four-scenario computation required approximately 7128 s.

EnergiesVol. 19(18)
Tianjin University of Technology (CN), North China Electric Power University (CN), Nanjing Institute of Technology (CN), China Electric Power Research Institute
Openalex Percentile: Top 20%
Optimal Power Flow Distribution
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A Multi-Stage Resilience Enhancement Method for Distribution Systems Considering Faulty Remote-Controlled Switches and Crew Dispatch — Xinyun Lu, Jiancun Liu, et al. · Energies (2026) | TGRS Research Map | TGRS