Optimized path planning for electric vehicle routing and charging

Mahnoosh Alizadeh; Hoi To Wai; Anna Scaglione; Andrea Goldsmith; Yue Yue Fan; Tara Javidi

doi:10.1109/ALLERTON.2014.7028431

Optimized path planning for electric vehicle routing and charging

Mahnoosh Alizadeh, Hoi To Wai, Anna Scaglione, Andrea Goldsmith, Yue Yue Fan, Tara Javidi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

44 Scopus citations

Abstract

We consider the decision problem of an individual EV owner who needs to pick a travel path including its charging locations and associated charge amount under time-varying traffic conditions as well as dynamic location-based electricity pricing. We show that the problem is equivalent to finding the shortest path on an extended transportation graph. In particular, we extend the original transportation graph through the use of virtual links with negative energy requirements to represent charging options available to the user. Using these extended transportation graphs, we then study the collective effects of a large number of EV owners solving the same type of path planning problem under the following control strategies: 1) a social planner decides the optimal route and charge strategy of all EVs; 2) users reach an equilibrium under locationally-variant electricity prices that are constant over time; 3) the transportation and power systems are separately controlled through marginal pricing strategies, not taking into account their mutual effect on one another. We numerically show that this disjoint type of control can lead to instabilities in the grid as well as inefficient system operation.

Original language	English (US)
Title of host publication	2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	25-32
Number of pages	8
ISBN (Electronic)	9781479980093
DOIs	https://doi.org/10.1109/ALLERTON.2014.7028431
State	Published - Jan 30 2014
Externally published	Yes
Event	2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 - Monticello, United States Duration: Sep 30 2014 → Oct 3 2014

Publication series

Name	2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014

Other

Other	2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014
Country/Territory	United States
City	Monticello
Period	9/30/14 → 10/3/14

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications

Access to Document

10.1109/ALLERTON.2014.7028431

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Alizadeh, M., Wai, H. T., Scaglione, A., Goldsmith, A., Fan, Y. Y., & Javidi, T. (2014). Optimized path planning for electric vehicle routing and charging. In 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 (pp. 25-32). Article 7028431 (2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ALLERTON.2014.7028431

Alizadeh, Mahnoosh ; Wai, Hoi To ; Scaglione, Anna et al. / Optimized path planning for electric vehicle routing and charging. 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 25-32 (2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014).

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title = "Optimized path planning for electric vehicle routing and charging",

abstract = "We consider the decision problem of an individual EV owner who needs to pick a travel path including its charging locations and associated charge amount under time-varying traffic conditions as well as dynamic location-based electricity pricing. We show that the problem is equivalent to finding the shortest path on an extended transportation graph. In particular, we extend the original transportation graph through the use of virtual links with negative energy requirements to represent charging options available to the user. Using these extended transportation graphs, we then study the collective effects of a large number of EV owners solving the same type of path planning problem under the following control strategies: 1) a social planner decides the optimal route and charge strategy of all EVs; 2) users reach an equilibrium under locationally-variant electricity prices that are constant over time; 3) the transportation and power systems are separately controlled through marginal pricing strategies, not taking into account their mutual effect on one another. We numerically show that this disjoint type of control can lead to instabilities in the grid as well as inefficient system operation.",

author = "Mahnoosh Alizadeh and Wai, {Hoi To} and Anna Scaglione and Andrea Goldsmith and Fan, {Yue Yue} and Tara Javidi",

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Alizadeh, M, Wai, HT, Scaglione, A, Goldsmith, A, Fan, YY & Javidi, T 2014, Optimized path planning for electric vehicle routing and charging. in 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014., 7028431, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014, Institute of Electrical and Electronics Engineers Inc., pp. 25-32, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014, Monticello, United States, 9/30/14. https://doi.org/10.1109/ALLERTON.2014.7028431

Optimized path planning for electric vehicle routing and charging. / Alizadeh, Mahnoosh; Wai, Hoi To; Scaglione, Anna et al.
2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 25-32 7028431 (2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - We consider the decision problem of an individual EV owner who needs to pick a travel path including its charging locations and associated charge amount under time-varying traffic conditions as well as dynamic location-based electricity pricing. We show that the problem is equivalent to finding the shortest path on an extended transportation graph. In particular, we extend the original transportation graph through the use of virtual links with negative energy requirements to represent charging options available to the user. Using these extended transportation graphs, we then study the collective effects of a large number of EV owners solving the same type of path planning problem under the following control strategies: 1) a social planner decides the optimal route and charge strategy of all EVs; 2) users reach an equilibrium under locationally-variant electricity prices that are constant over time; 3) the transportation and power systems are separately controlled through marginal pricing strategies, not taking into account their mutual effect on one another. We numerically show that this disjoint type of control can lead to instabilities in the grid as well as inefficient system operation.

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Alizadeh M, Wai HT, Scaglione A, Goldsmith A, Fan YY, Javidi T. Optimized path planning for electric vehicle routing and charging. In 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 25-32. 7028431. (2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014). doi: 10.1109/ALLERTON.2014.7028431

Optimized path planning for electric vehicle routing and charging

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