A Joint Industrial Engineering and Urban Planning Approach for Designing an Optimal Electric Vehicle Charging Network

This research aims to determine the optimal locations for electric vehicle charging stations (EVCSs) in urban and suburban areas of Louisville, Kentucky. We apply a combined methodology integrating industrial engineering (IE) and urban planning (UP) approaches. The IE methodology is an optimization-simulation framework that takes forecasted charging demands and provides the optimal strategic location and capacities of EVCSs by solving a mixed integer linear problem (MILP). Subsequently, an agent-based simulation model is developed to study the behavior of the electric vehicles (EVs) fleet to account for their dynamic and stochastic nature. It also allows monitoring of the charging stations' status (i.e., queue length and average waiting time) during the study period. In addition to operational efficiency, our network design also considers various community related factors such as population size, unemployment rate, traffic conditions, amenities, and economic growth projection often used by location analysis in urban planning. A total of 11 factors are weighted by stakeholders and used to evaluate 560 Traffic Analysis Zones (TAZ) in Louisville. The final recommendations are the top five locations for EVCSs based on the integrated outcome of engineering and urban planning analyses.