2022 article
Hierarchical Optimization of Charging Infrastructure Design and Facility Utilization
Mirheli, A., & Hajibabai, L. (2022, January 21). IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS.
author keywords: Optimization; Costs; Batteries; Vehicle dynamics; Electric vehicle charging; Charging stations; Pricing; Global optimal; bi-level; hierarchical optimization; network design; dynamic pricing; equilibrium; electric vehicle; charging facility
open access via ieeexplore.ieee.org (publisher PDF)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(Web of Science)
9. Industry, Innovation and Infrastructure
(OpenAlex)
11. Sustainable Cities and Communities
(Web of Science)
13. Climate Action
(Web of Science)
Source: Web Of Science
Added: February 7, 2022
This study proposes a bi-level optimization program to represent the electric vehicle (EV) charging infrastructure design and utilization management problem with user-equilibrium (UE) decisions. The upper level aims to minimize total facility deployment costs and maximize the revenue generated from EV charging collections, while the lower level aims to minimize the EV users’ travel times and charging expenses. An iterative technique is implemented to solve the bi-level mixed-integer non-linear program that generates theoretical lower and upper bounds to the bi-level model and solves it to global optimality. A set of conditions are evaluated to show the convergence of the algorithm in a finite number of iterations. The numerical results, based on three demand levels, indicate that the proposed bi-level model can effectively determine the optimal charging facility location, physical capacity, and demand-responsive pricing scheme. The average charging price in medium demand level is increased by 38.21% compared to the lower level demand due to the surge in charging needs and highly utilized charging stations.