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Mobile power sources pre‐allocation and dispatch strategy in power‐transportation coupled network under extreme weather

Guochen Fan, Zhaobin Du, Xiaoke Lin, Nanxing Chen

2023IET Renewable Power Generation11 citationsDOIOpen Access PDF

Abstract

Abstract This study introduces a strategy for the pre‐allocation and dispatch of mobile power sources (MPSs) within a power‐transportation coupled network, targeting efficient distribution network fault recovery under extreme weather conditions. The strategy incorporates the Dijkstra algorithm and blind number theory to analyse the MPS driving path and generate fault scenarios respectively, considering the effects of extreme weather on traffic capacity and distribution network fault rate. The MPS pre‐allocation model, formulated to minimize the load outage loss, MPS investment, and driving fuel cost, provides a foundation for optimization of the dispatch process. The dispatch optimization model adapts to dynamic information from the power‐transportation coupled network to make decisions on load restoration sequencing and MPS driving path. The effectiveness of the proposed strategy is demonstrated through an application to the IEEE 33‐node distribution system and a corresponding 33‐node transportation network.

Topics & Concepts

Dijkstra's algorithmFault (geology)Node (physics)Computer sciencePower (physics)Path (computing)Real-time computingMathematical optimizationReliability engineeringEngineeringShortest path problemComputer networkMathematicsGeologyStructural engineeringTheoretical computer scienceQuantum mechanicsGraphPhysicsSeismologyOptimal Power Flow DistributionMicrogrid Control and OptimizationIslanding Detection in Power Systems
Mobile power sources pre‐allocation and dispatch strategy in power‐transportation coupled network under extreme weather | Litcius