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Bibliographic Details
Main Authors: Christeson, Tyler, Khodaei, Amin, Fan, Rui
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.00736
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author Christeson, Tyler
Khodaei, Amin
Fan, Rui
author_facet Christeson, Tyler
Khodaei, Amin
Fan, Rui
contents The power grid is the foundation of modern society, however extreme weather events have increasingly caused widespread outages. Enhancing grid resilience is therefore critical to maintaining secure and reliable operations. In disaster relief and restoration, vehicle-to-grid (V2G) technology allows electric vehicles (EVs) to serve as mobile energy resources by discharging to support critical loads or regulating grid frequency as needed. Effective V2G operation requires coordinated charging and discharging of many EVs through optimization. Similarly, in grid restoration, EVs must be strategically routed to affected areas, forming the mobile charging station placement (CSP) problem, which presents another complex optimization challenge. This work reviews state-of-the-art optimization methods for V2G and mobile CSP applications, outlines their limitations, and explores how quantum computing (QC) could overcome current computational bottlenecks. A QC-focused perspective is presented on enhancing grid resilience and accelerating restoration as extreme weather events grow more frequent and severe.
format Preprint
id arxiv_https___arxiv_org_abs_2511_00736
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Quantum Computing for EVs to Enhance Grid Resilience and Disaster Relief: Challenges and Opportunities
Christeson, Tyler
Khodaei, Amin
Fan, Rui
Systems and Control
The power grid is the foundation of modern society, however extreme weather events have increasingly caused widespread outages. Enhancing grid resilience is therefore critical to maintaining secure and reliable operations. In disaster relief and restoration, vehicle-to-grid (V2G) technology allows electric vehicles (EVs) to serve as mobile energy resources by discharging to support critical loads or regulating grid frequency as needed. Effective V2G operation requires coordinated charging and discharging of many EVs through optimization. Similarly, in grid restoration, EVs must be strategically routed to affected areas, forming the mobile charging station placement (CSP) problem, which presents another complex optimization challenge. This work reviews state-of-the-art optimization methods for V2G and mobile CSP applications, outlines their limitations, and explores how quantum computing (QC) could overcome current computational bottlenecks. A QC-focused perspective is presented on enhancing grid resilience and accelerating restoration as extreme weather events grow more frequent and severe.
title Quantum Computing for EVs to Enhance Grid Resilience and Disaster Relief: Challenges and Opportunities
topic Systems and Control
url https://arxiv.org/abs/2511.00736