Electric Vehicle Charging Stations Placement Optimization in Vietnam Using Mixed-Integer Nonlinear Programming Model

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Hauptverfasser: Truc, Quynh Vu, Hien, Minh Ha, Tuan, Hai Vu
Format: Preprint
Veröffentlicht: 2024
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author Truc, Quynh Vu
Hien, Minh Ha
Tuan, Hai Vu
author_facet Truc, Quynh Vu
Hien, Minh Ha
Tuan, Hai Vu
contents Vietnam is viewed as one of the promising markets for electric vehicles (EVs), especially automobiles, when it is predicted to reach 1 million in 2028 and 3.5 million in 2040. However, the lack of charging station infrastructure has hindered the growth rate of EVs in this country. This study aims to propose an optimization model using Mixed-Integer Nonlinear Programming to implement an optimal location strategy for EVs charging stations in Ho Chi Minh City. The problem is solved by Gurobi using the Brand-and-Cut method. There are two perspectives, including Charging Station Operators and EV users. In addition, 7 kinds of costs are considered. From 1509 Point of Interest and 199 residential areas, 134 POIs were chosen with 923 charging stations to fully satisfy the customer demand. Furthermore, the effectiveness of the proposed model is proved by a minor MIP Gap and running in a short time with full feasibility.
format Preprint
id arxiv_https___arxiv_org_abs_2412_16025
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Electric Vehicle Charging Stations Placement Optimization in Vietnam Using Mixed-Integer Nonlinear Programming Model
Truc, Quynh Vu
Hien, Minh Ha
Tuan, Hai Vu
Computational Engineering, Finance, and Science
Vietnam is viewed as one of the promising markets for electric vehicles (EVs), especially automobiles, when it is predicted to reach 1 million in 2028 and 3.5 million in 2040. However, the lack of charging station infrastructure has hindered the growth rate of EVs in this country. This study aims to propose an optimization model using Mixed-Integer Nonlinear Programming to implement an optimal location strategy for EVs charging stations in Ho Chi Minh City. The problem is solved by Gurobi using the Brand-and-Cut method. There are two perspectives, including Charging Station Operators and EV users. In addition, 7 kinds of costs are considered. From 1509 Point of Interest and 199 residential areas, 134 POIs were chosen with 923 charging stations to fully satisfy the customer demand. Furthermore, the effectiveness of the proposed model is proved by a minor MIP Gap and running in a short time with full feasibility.
title Electric Vehicle Charging Stations Placement Optimization in Vietnam Using Mixed-Integer Nonlinear Programming Model
topic Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2412.16025