https://scholars.lib.ntu.edu.tw/handle/123456789/625016
Title: | Optimal routing for electric vehicle charging systems with stochastic demand: A heavy traffic approximation approach | Authors: | Hung Y.-C PakHai Lok H Michailidis G. YING-CHAO HUNG |
Keywords: | Convex optimization; Electric vehicle; Heavy traffic approximation; Mean response time; Routing | Issue Date: | 2022 | Journal Volume: | 299 | Journal Issue: | 2 | Start page/Pages: | 526-541 | Source: | European Journal of Operational Research | 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. © 2021 Elsevier B.V. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111478653&doi=10.1016%2fj.ejor.2021.06.058&partnerID=40&md5=18f582e2ac35010bbf91fafbd86f02a9 https://scholars.lib.ntu.edu.tw/handle/123456789/625016 |
ISSN: | 03772217 | DOI: | 10.1016/j.ejor.2021.06.058 | SDG/Keyword: | Charging (batteries); Constrained optimization; Electric vehicles; Routing algorithms; Stochastic systems; Approximation approach; Charging systems; Convex optimisation; Electric vehicle charging; Heavy-traffic approximation; Mean response time; Optimal routing; Routing strategies; Routings; Stochastic-demand; Convex optimization |
Appears in Collections: | 工業工程學研究所 |
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