Electric Vehicle Route Optimization Under Time-of-Use Electricity Pricing

Ham, Andy; Park, Myoung-Ju

doi:10.1109/access.2021.3063316

Cited by 14 publications

(10 citation statements)

References 35 publications

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“…The problem under study is linked to several variants of the Vehicle Routing Problem (VRP), namely Solar-VRP [29], Hybrid-VRP [30], Green-VRP [31], and Electric-VRP [32]. Solar-VRP seeks to optimize the route and speed of a solar-powered electric vehicle in a single-source singledestination tour such that power consumption is balanced by harnessed solar energy.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones

Alyassi

Khonji

Karapetyan

et al. 2023

IEEE Trans. Automat. Sci. Eng.

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Unmanned aerial vehicles (UAVs), commonly known as drones, are being increasingly deployed throughout the globe as a means to streamline monitoring, inspection, mapping, and logistic routines. When dispatched on autonomous missions, drones require an intelligent decision-making system for trajectory planning and tour optimization. Given the limited capacity of their onboard batteries, a key design challenge is to ensure the underlying algorithms can efficiently optimize the mission objectives along with recharging operations during longhaul flights. With this in view, the present work undertakes a comprehensive study on automated tour management systems for an energy-constrained drone: (1) We construct a machine learning model that estimates the energy expenditure of typical multi-rotor drones while accounting for real-world aspects and extrinsic meteorological factors. (2) Leveraging this model, the joint program of flight mission planning and recharging optimization is formulated as a multi-criteria Asymmetric Traveling Salesman Problem (ATSP), wherein a drone seeks for the time-optimal energy-feasible tour that visits all the target sites and refuels whenever necessary. (3) We devise an efficient approximation algorithm with provable worst-case performance guarantees and implement it in a drone management system, which supports real-time flight path tracking and re-computation in dynamic environments. (4) The effectiveness and practicality of the proposed approach are validated through extensive numerical simulations as well as real-world experiments. Note to Practitioners-This study is stimulated by the need for developing pragmatic and provably efficient automated tour management systems for UAVs deployed on energy-constrained, long-distance flight missions. As such, UAVs provide a nifty platform for facilitating environmental monitoring, disaster management, transport of medical supplies, as well as expediting last-mile deliveries. However, existing path planners generally Manuscript

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Section: Related Workmentioning

confidence: 99%

Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones

Alyassi

Khonji

Karapetyan

et al. 2023

IEEE Trans. Automat. Sci. Eng.

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“…In the power system, there are two representative tariff systems that charge fees at EV charging facility. One is real-time pricing, which determines a rate according to real-time power supplement [28], [29], and the other is ToU pricing, which determines a differential rate for each time period based on accumulated data [30], [31]. In the case of real-time pricing, electricity rates are determined in consideration of changes in power supplement or renewable energy generation in a short time period.…”

Section: Second Stage Power Operation: Optimization Processmentioning

confidence: 99%

Power Scheduling Scheme for a Charging Facility Considering the Satisfaction of Electric Vehicle Users

et al. 2022

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This paper proposes a novel user-preference-aware power scheduling scheme for application at an electric vehicle (EV) charging facility. Here, the preference of the EV user is characterized as a utility function by considering two different factors: 1) a satisfaction factor according to the charged energy, and 2) payment for the received charging service. As a key component of the power scheduling method, this paper proposes a two-stage power charging method and analyzes the advantage of the proposed method from a monetary perspective. In addition, this paper analyzes the economic benefits of a charging facility and EVs using the single-leader, multi-follower Stackelkberg game. By showing the existence of a unique best response for each participant, this paper presents the improvement of financial profit of EV users and charging facility through comparison with the case where the charging facility does not apply a proper power management scheme. Based on the actual world datasets, this paper shows that the proposed power scheduling scheme is feasible for actual environment. With satisfying the constraints, it is possible to reduce overall electricity cost up to 8.59% compared to the case without considering the peak power in EV charging facility.

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“…Constraints ( 6) and ( 7) ensure that node j will be visited before node n+j for every paired orders. Constraint (8) ensures that the origin and destination nodes are visited by the same vehicle for non Express-Pool orders. Similarly, Constraint (9) ensures that the origin and destination nodes are visited by the same vehicle for Express-Pool orders.…”

Section: A Cp1mentioning

confidence: 99%

Dial-a-Ride Problem With Meeting Point Feature Known-as Express-Pool

Ham

2021

IEEE Access

Self Cite

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This study extends a dial-a-ride problem by considering (1) Express-Pool and (2) Friend-Only. Uber provides an advanced feature called Express-Pool where passengers are willing to walk a short distance to be picked up and be dropped off somewhere close to destination in exchange for a reduced fare. Tesla's 2020 Robotaxi plan includes that vehicle owners will be able to determine if their vehicles can be shared with friends and co-workers only. For this evolving transportation problem, the contributions of this paper are threefold. First, we define DARP with Express-Pool and Friend-Only. Second, a novel constraint programming approach is proposed. Third, a two-phase approach based on warm-start method is devised to improve the performance of the base model.

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Electric Vehicle Route Optimization Under Time-of-Use Electricity Pricing

Abstract: VOLUME XX, 2017 1. Third, a rescheduling approach based on warm-start method is proposed to handle a dynamic order in real-time. Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 14 publications

References 35 publications

Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones

Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones

Power Scheduling Scheme for a Charging Facility Considering the Satisfaction of Electric Vehicle Users

Dial-a-Ride Problem With Meeting Point Feature Known-as Express-Pool

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