A Quantum Optimization Algorithm for Optimal Electric Vehicle Charging Station Placement for Intercity Trips

Radvand, Tina; Talebpour, Alireza; Illinois Center for Transportation; University of Illinois at Urbana-Champaign. Department of Civil and Environmental Engineering; Center for Connected and Automated Transportation (CCAT); University of Michigan Transportation Research Institute

doi:10.36501/0197-9191/24-028

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A Quantum Optimization Algorithm for Optimal Electric Vehicle Charging Station Placement for Intercity Trips

2024-12-01
By Radvand, Tina ; Talebpour, Alireza

English

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Details:

Creators:

Radvand, Tina ; Talebpour, Alireza

Radvand, Tina ; Talebpour, Alireza Less -
Corporate Creators:

Illinois Center for Transportation ; University of Illinois at Urbana-Champaign. Department of Civil and Environmental Engineering ; Center for Connected and Automated Transportation (CCAT) ; University of Michigan Transportation Research Institute

Illinois Center for Transportation ; University of Illinois at Urbana-Champaign. Department of Civil and Environmental Engineering ; Center for Connected and Automated Transportation (CCAT) ; University of Michigan Transportation Research Institute Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Algorithms Electric Vehicle Charging Networks Optimization Quantum Mechanics Regional Transportation
Publication/ Report Number:

ICT-24-028
DOI:

https://doi.org/10.36501/0197-9191/24-028
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

Illinois Center for Transportation
Abstract:

Electric vehicles (EVs) play a significant role in enhancing the sustainability of transportation systems. However, their widespread adoption is hindered by inadequate public charging infrastructure, particularly to support long-distance travel. Identifying optimal charging station locations in large transportation networks presents a well-known NP-hard combinatorial optimization problem, as the search space grows exponentially with the number of potential charging station locations. This report introduces a quantum search-based optimization algorithm designed to enhance the efficiency of solving this NP-hard problem for both corridors and transportation networks. By leveraging quantum parallelism, amplitude amplification, and quantum phase estimation as a subroutine, the optimal solution is identified with a quadratic improvement in complexity compared to classical exact methods, such as branch and bound. The detailed design and complexity of a resource-efficient quantum circuit are discussed.
Format:

PDF
Funding:

69A3552348301
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha-512:0fa94f88d798c4b748990016fc0a957066b99547a6911425c2b33076a5077b4be8ff940e2bc984a95b488fe33f3797e019c51e942ff345142bdcd694b8c09672
Download URL:

https://rosap.ntl.bts.gov/view/dot/79167/dot_79167_DS1.pdf
File Type:

[PDF-4.93 MB]