Incorporating demand dynamics in multi-period capacitated fast-charging location planning for electric vehicles

- A multi-period capacitated flow refueling location problem is developed to capture demand dynamics for EV charging station planning.
- Various demand dynamics are defined as a function of path-specific/overall charging opportunities as well as natural growth of travel demand.
- A heuristic method is developed to handle nonlinearity and computational challenges of the proposed formulation by enumerating a subset of cases.
- A case study based on Northeastern NY-DC-Boston corridor examines flow coverage and market share for two different demand dynamics.
- It is observed that the demand dynamics is a crucial component in planning of charging infrastructure and transportation sustainability.

We develop a multi-period capacitated flow refueling location problem for electric vehicles (EVs) as the EV market responds to the charging infrastructure. The optimization model will help us determine the optimal location of level 3 chargers as well as the number of charging modules at each station over multiple time periods. Our model can also be applied to fast-filling gaseous alternative fuel vehicles under similar assumptions. We define a number of demand dynamics, including flow demand growth as a function of charging opportunities on path as well as natural demand growth independent of charging infrastructure. We also present an alternative objective function of maximizing electric vehicle demand in addition to maximizing flow coverage. A case study based on a road network around Washington, D.C., New York City, and Boston is presented to provide numerical experiments related to demand dynamics, showing the potential problems in multi-period planning.