Model for Optimized EVSE Deployment in Dense Urban Areas

Current trends and data show that Electric Vehicle (EV) adoption has significantly increased in the past years in the developed world and will continue to grow towards a 23% market penetration by 2030. An important challenge hindering this mobility transition is range anxiety in direct connection to infrastructure constraints related to the availability, cost and ease of access to suitable charging options. Starting from the existing situation we tackle the issue of new Electrical Vehicle Supply Equipment (EVSE) station installation in urban areas. We present an optimization model that accounts for EV density, usage, battery, capacity and estimated waiting time i.e. user comfort as decision support tool for service providers and city planners. The output yields optimal positions for new EVSE installations by maximising operator profit, user convenience or a weighted balance between the two. Mixed Integer Linear Programming (MILP) is used as a technique to solve the optimization problem with CPLEX/Matlab implementation. The model is suitable for both offline and online running as well as for multi-time period evaluation under dynamic constraint adjustments. The results show the feasibility of our approach based on real data from publicly available repositories such as Plugshare and EV registration records.