An Electric Vehicle Transitioning Framework for Public Fleet Planning

While electric vehicle (EV) use has proliferated in developed countries, emerging nations have lagged behind because they lack the resources to establish effective EV charging networks. To address this issue, this paper has developed a framework through scenario analysis that aims to minimize the costs involved in establishing such networks and provide policy makers with insights on how to accomplish this. A given set of public institutions possessing EV fleets were first grouped into zones using clustering algorithms. Mathematical models were then developed to identify optimal EV charging station locations serving the EV fleets of these organizations, with an objective to minimize the total cost. Factors such as EV range anxiety and human walking distance were imbedded into the framework, which was examined using real world data from three major cities in Morocco: Rabat, Casablanca, and Fes. With the framework, policy makers can make better planning decisions on EV transitioning.