Electric Distribution Network Restoration Strategy with Pre‐Deployment and Real‐Time Scheduling of Mobile Emergency Generators in Coupled Transportation Network

Mobile emergency generators (MEG) serve as critical emergency resources for enhancing distribution network restoration. Since the travel time of MEG in the transportation network will greatly affect the restoration speed of important loads, it is vital to take into account the routing problem of MEG in the transportation network when achieving MEG‐assisted distribution network restoration. In this context, this paper proposes a two‐stage restoration strategy considering pre‐event MEG allocation and after‐event restoration with real‐time scheduling of MEG. Specifically, first, the spatial coupling mode of distribution network and transportation network is analyzed, and multiple fault scenarios are generated based on the fragility curves of distribution network equipment under extreme weather conditions. Second, aiming to optimize the MEG dispatching path and maximizing the load restoration after extreme events, a pre‐event allocation model for MEGs is established. Then, focusing on the specific post‐event distribution network fault scenario, a multi‐period restoration model considering the real‐time dispatching of MEG is established. The real‐time routing and scheduling constraints of MEG in coupled distribution‐transportation networks and the operation constraints of distribution network are fully incorporated. Eventually, case studies on the coupled PG&E69 distribution network and 30‐node transportation network verify the effectiveness of the proposed restoration strategy. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

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Publication Details

Journal
IEEJ Transactions on Electrical and Electronic Engineering
Published
2026-01-23
DOI
https://doi.org/10.1002/tee.70253
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

Electric Distribution Network Restoration Strategy with Pre‐Deployment and Real‐Time Scheduling of Mobile Emergency Generators in Coupled Transportation Network

Wenqian Yin, Haoming Liu, Jian Wang, Jihang Cheng
IEEJ Transactions on Electrical and Electronic Engineering
Optimal Power Flow Distribution
article

Electric Distribution Network Restoration Strategy with Pre‐Deployment and Real‐Time Scheduling of Mobile Emergency Generators in Coupled Transportation Network

Wenqian Yin, Haoming Liu, Jian Wang, Jihang Cheng
article en

Abstract

Mobile emergency generators (MEG) serve as critical emergency resources for enhancing distribution network restoration. Since the travel time of MEG in the transportation network will greatly affect the restoration speed of important loads, it is vital to take into account the routing problem of MEG in the transportation network when achieving MEG‐assisted distribution network restoration. In this context, this paper proposes a two‐stage restoration strategy considering pre‐event MEG allocation and after‐event restoration with real‐time scheduling of MEG. Specifically, first, the spatial coupling mode of distribution network and transportation network is analyzed, and multiple fault scenarios are generated based on the fragility curves of distribution network equipment under extreme weather conditions. Second, aiming to optimize the MEG dispatching path and maximizing the load restoration after extreme events, a pre‐event allocation model for MEGs is established. Then, focusing on the specific post‐event distribution network fault scenario, a multi‐period restoration model considering the real‐time dispatching of MEG is established. The real‐time routing and scheduling constraints of MEG in coupled distribution‐transportation networks and the operation constraints of distribution network are fully incorporated. Eventually, case studies on the coupled PG&E69 distribution network and 30‐node transportation network verify the effectiveness of the proposed restoration strategy. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

IEEJ Transactions on Electrical and Electronic Engineering
Nanjing Tech University (CN), Hohai University (CN)
Sustainable cities and communities
Openalex Percentile: Top 80%
Optimal Power Flow Distribution
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