Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles

The adoption of autonomous electric vehicles (AEVs) offers an opportunity to decarbonize the transportation sector while eliminating the human errors in driving accidents. However, adopting AEVs may impose challenges to the operation of power distribution systems to ensure the availability of power...

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Main Authors: Avishan Bagherinezhad, Mahnoosh Alizadeh, Masood Parvania
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10382159/
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author Avishan Bagherinezhad
Mahnoosh Alizadeh
Masood Parvania
author_facet Avishan Bagherinezhad
Mahnoosh Alizadeh
Masood Parvania
author_sort Avishan Bagherinezhad
collection DOAJ
description The adoption of autonomous electric vehicles (AEVs) offers an opportunity to decarbonize the transportation sector while eliminating the human errors in driving accidents. However, adopting AEVs may impose challenges to the operation of power distribution systems to ensure the availability of power for charging a growing number of AEVs at different times and locations. This paper takes an opportunistic look at this problem and develops a rolling horizon model for coordinating the operation of electric autonomous ride-hailing systems with power distribution systems. The proposed model incorporates the most recent real-time information and the future expected value of energy level, spatial and temporal location of AEV fleet, traffic data, and passenger demand. Using this data, the proposed model adopts a rolling horizon approach to optimize the routing of AEVs to serve spatio-temporal passenger demand across the transportation network, while optimizing the time and location of AEVs charging to ensure the availability of energy to serve the passenger demand, and satisfying the operational constraints of the power distribution system. The proposed model is implemented on a test transportation system, coupled with the IEEE 33-bus test power distribution system. The numerical results demonstrate the capability of the proposed model in ensuring the reliability and quality of service for both electric autonomous ride-hailing and power distribution systems.
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spelling doaj-art-335b90a908ff4b00954d0a80bbd2c38b2025-01-21T00:03:14ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102024-01-01119410310.1109/OAJPE.2023.334797210382159Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric VehiclesAvishan Bagherinezhad0Mahnoosh Alizadeh1Masood Parvania2https://orcid.org/0000-0002-8891-7010Department of Electrical and Computer Engineering, The University of Utah, Salt Lake City, UT, USADepartment of Electrical and Computer Engineering, University of California at Santa Barbara, Santa Barbara, CA, USADepartment of Electrical and Computer Engineering, The University of Utah, Salt Lake City, UT, USAThe adoption of autonomous electric vehicles (AEVs) offers an opportunity to decarbonize the transportation sector while eliminating the human errors in driving accidents. However, adopting AEVs may impose challenges to the operation of power distribution systems to ensure the availability of power for charging a growing number of AEVs at different times and locations. This paper takes an opportunistic look at this problem and develops a rolling horizon model for coordinating the operation of electric autonomous ride-hailing systems with power distribution systems. The proposed model incorporates the most recent real-time information and the future expected value of energy level, spatial and temporal location of AEV fleet, traffic data, and passenger demand. Using this data, the proposed model adopts a rolling horizon approach to optimize the routing of AEVs to serve spatio-temporal passenger demand across the transportation network, while optimizing the time and location of AEVs charging to ensure the availability of energy to serve the passenger demand, and satisfying the operational constraints of the power distribution system. The proposed model is implemented on a test transportation system, coupled with the IEEE 33-bus test power distribution system. The numerical results demonstrate the capability of the proposed model in ensuring the reliability and quality of service for both electric autonomous ride-hailing and power distribution systems.https://ieeexplore.ieee.org/document/10382159/Autonomous electric vehicleride-hailing servicespower distribution systemvehicle charging and routing
spellingShingle Avishan Bagherinezhad
Mahnoosh Alizadeh
Masood Parvania
Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles
IEEE Open Access Journal of Power and Energy
Autonomous electric vehicle
ride-hailing services
power distribution system
vehicle charging and routing
title Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles
title_full Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles
title_fullStr Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles
title_full_unstemmed Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles
title_short Rolling Horizon Approach for Real-Time Charging and Routing of Autonomous Electric Vehicles
title_sort rolling horizon approach for real time charging and routing of autonomous electric vehicles
topic Autonomous electric vehicle
ride-hailing services
power distribution system
vehicle charging and routing
url https://ieeexplore.ieee.org/document/10382159/
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AT mahnooshalizadeh rollinghorizonapproachforrealtimechargingandroutingofautonomouselectricvehicles
AT masoodparvania rollinghorizonapproachforrealtimechargingandroutingofautonomouselectricvehicles