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Optimal routing for electric vehicle charging systems with stochastic demand: A heavy traffic approximation approach

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  • Hung, Ying-Chao
  • PakHai Lok, Horace
  • Michailidis, George

Abstract

We consider a general electric vehicle (EV) charging system with stochastic demand, demand request locations, and predetermined charging facilities (including charging station locations and charger capacities). The objective is to design a good routing strategy that accommodates well demand-request dynamics so as to satisfy the charging system’s stability constraints and also minimize the EV’s mean response time. We introduce a class of flexible and measurement-based routing policies called “partition-based random routing” (PBRR) and show that the performance measure of interest can be formulated as a constrained optimization problem with a convex objective function when the system is heavily loaded. This formulation enables us to establish strong theoretical results that are in aid of finding the optimal routing solution; however, in practice, finding this solution requires rather involved numerical calculations. To that end, we propose a surrogate, easy to design and implement, optimization algorithm for finding the desired optimal routing solution. Numerical work based on synthetic data shows that the performance of the developed routing strategy and its fast implementation is highly satisfactory for a number of system settings.

Suggested Citation

  • Hung, Ying-Chao & PakHai Lok, Horace & Michailidis, George, 2022. "Optimal routing for electric vehicle charging systems with stochastic demand: A heavy traffic approximation approach," European Journal of Operational Research, Elsevier, vol. 299(2), pages 526-541.
    • Handle: RePEc:eee:ejores:v:299:y:2022:i:2:p:526-541
    DOI: 10.1016/j.ejor.2021.06.058
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    Cited by:

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    2. Pegah Alaee & Julius Bems & Amjad Anvari-Moghaddam, 2023. "A Review of the Latest Trends in Technical and Economic Aspects of EV Charging Management," Energies, MDPI, vol. 16(9), pages 1-28, April.
    3. Kinene, Alan & Birolini, Sebastian & Cattaneo, Mattia & Granberg, Tobias Andersson, 2023. "Electric aircraft charging network design for regional routes: A novel mathematical formulation and kernel search heuristic," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1300-1315.
    4. Witt Andreas, 2023. "Determination of the Number of Required Charging Stations on a German Motorway Based on Real Traffic Data and Discrete Event-Based Simulation," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 1-11, January.

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