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

TL;DR

This paper develops a mixed-integer nonlinear programming model to optimize the placement of EV charging stations in Ho Chi Minh City, addressing infrastructure gaps and supporting Vietnam's EV market growth.

Contribution

It introduces a novel optimization model for EV charging station placement considering multiple costs and perspectives, solved efficiently with Gurobi.

Findings

134 POIs selected for 923 charging stations

Model achieves low MIP gap and quick solution times

Full demand satisfaction for EV users

Abstract

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.