Enhancing resilient distribution networks through proactive topology optimization and robotaxi dispatch coordination

Robotaxi (RT), a recently emerging class of autonomous ride-hailing electric taxis, offer significant potential to enhance power distribution network (PDN) resilience through coordinated operation, leveraging their fully dispatchable nature. The charging behavior of electric vehicles (EVs) naturally couples PDN with the road network (RN). However, some studies on PDN resilience overlook the spatial correlation of disaster impacts on both the RN and PDN, which may lead to suboptimal strategies by limiting accurate infrastructure condition assessment and effective coordination between transportation and power systems. Thus, this paper first develops an infrastructure performance degradation model (IPDM) to quantify the joint impact of extreme disasters on both RN and PDN, further analyzing their influence on charging demand variation. Building on this, a coordination framework is proposed to enhance PDN resilience under extreme disasters. This framework innovatively leverages RT fleets as mobile flexibility resources and integrates charging management with proactive PDN topology optimization, including placement of soft open points (SOPs) and circuit breakers (CBs) and PDN reconfiguration. Case studies demonstrate that the proposed framework not only improves PDN resilience but also reduces associated economic cost. Furthermore, sensitivity analysis of varying RT penetration levels on resilience strategies is systematically examined, highlighting the potential of RTs in supporting switch planning. • Robotaxi-enabled switch planning for transport-power coordination. • Disaster-induced degradation model for road-grid coupled network. • Coordinated Robotaxi dispatch to cut charging delays and revenue loss.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2026-02-14
DOI
https://doi.org/10.1016/j.ijepes.2026.111682
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
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article

Enhancing resilient distribution networks through proactive topology optimization and robotaxi dispatch coordination

Ziyao Wang, Yufeng Wu, Y.L. Gong, Zhenning Pan et al.
International Journal of Electrical Power & Energy Systems
Electric Vehicles and Infrastructure
article

Enhancing resilient distribution networks through proactive topology optimization and robotaxi dispatch coordination

Ziyao Wang, Yufeng Wu, Y.L. Gong, Zhenning Pan, Wencong Xiao, Tao Yu
article en

Abstract

Robotaxi (RT), a recently emerging class of autonomous ride-hailing electric taxis, offer significant potential to enhance power distribution network (PDN) resilience through coordinated operation, leveraging their fully dispatchable nature. The charging behavior of electric vehicles (EVs) naturally couples PDN with the road network (RN). However, some studies on PDN resilience overlook the spatial correlation of disaster impacts on both the RN and PDN, which may lead to suboptimal strategies by limiting accurate infrastructure condition assessment and effective coordination between transportation and power systems. Thus, this paper first develops an infrastructure performance degradation model (IPDM) to quantify the joint impact of extreme disasters on both RN and PDN, further analyzing their influence on charging demand variation. Building on this, a coordination framework is proposed to enhance PDN resilience under extreme disasters. This framework innovatively leverages RT fleets as mobile flexibility resources and integrates charging management with proactive PDN topology optimization, including placement of soft open points (SOPs) and circuit breakers (CBs) and PDN reconfiguration. Case studies demonstrate that the proposed framework not only improves PDN resilience but also reduces associated economic cost. Furthermore, sensitivity analysis of varying RT penetration levels on resilience strategies is systematically examined, highlighting the potential of RTs in supporting switch planning. • Robotaxi-enabled switch planning for transport-power coordination. • Disaster-induced degradation model for road-grid coupled network. • Coordinated Robotaxi dispatch to cut charging delays and revenue loss.

International Journal of Electrical Power & Energy SystemsVol. 176
University of Macau (MO), City University of Macau (MO), South China University of Technology (CN)
Openalex Percentile: Top 55%
Electric Vehicles and Infrastructure
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