Using Statewide Transportation Planning Model to Forecast Demand for Electric Vehicle Charging at Stations Along Intercity Highways

Abstract

The availability of Charging Stations (CSs) with adequate capacity is critical for the growth in ownership and usage of Electric Vehicles (EVs). In the United States, the state Departments of Transportation (DOTs) are responsible for planning CSs along the Interstate, national, and state highways. While the state DOTs have their Statewide Transportation Planning Models (STPMs), most of these models do not represent EVs internally. The state DOTs can only rely on the existing STPMs to forecast the demand for EV charging at specific CS locations in a state’s highway network. This research proposes a methodology that utilizes an existing STPM, EV and non-EV vehicle registration data, and hourly traffic volumes at strategic counting stations to predict the hourly demand for EV charging (charging port occupancy) at proposed CSs. This approach first estimates the volume of all passenger cars that will pass the vicinity of a CS along intercity highways, and identifies the Traffic Analysis Zones (TAZs) of their trip origins. Based on the EV adoption rates of the TAZs, EV range, and EV owner’s charging behavior, the methodology forecasts the volume of EVs that pass the vicinity of a CS and the number of EVs that will stop at the CS to charge every hour of the day. An example problem demonstrated the application of the methodology in the State of Texas. It not only forecasted the hourly occupancy at CSs along three major corridors, but also demonstrated how to determine the capacities of the CSs. The challenges of using the existing STPM and their solutions are discussed. This proposed methodology enables the state DOTs to forecast the demand for EV charging and the capacities at the proposed CSs along intercity highways, thus allowing the DOTs to apply for federal funds to accelerate the deployment of the CSs. (298 words)