Highly-resolved modeling of personal transportation energy consumption in the United States

• Modeling primary energy consumption for personal transportation in the United States.
• Behavior of drivers has been simulated in order to establish when driving events occur and the length of each event.
• Realistic driving profiles for each driving event are generated using a stochastic model.
• The model allows for comparing the initial cost of different vehicles and their expected energy-use operating cost.
• Evaluation of the impact of PEVs on the electric grid – especially at the distribution level – can be performed.

This paper centers on the estimation of the total primary energy consumption for personal transportation in the United States, to include gasoline and/or electricity consumption, depending on vehicle type. The bottom-up sector-based estimation method introduced here contributes to a computational tool under development at The Ohio State University for assisting decision making in energy policy, pricing, and investment.In order to simulate highly-resolved consumption profiles three main modeling steps are needed: modeling the behavior of drivers, generating realistic driving profiles, and simulating energy consumption of different kinds of vehicles.The modeling proposed allows for evaluating the impact of plug-in electric vehicles on the electric grid – especially at the distribution level. It can serve as a tool to compare different vehicle types and assist policy-makers in estimating their impact on primary energy consumption and the role transportation can play to reduce oil dependency.