The Role of Driver Behavior in Moving the Electric Grid to Zero Emissions

As we move towards more renewable resources, the ability to produce electricity in time with demand diminishes. Instead, rises a need for energy storage or the ability to produce electricity when renewables allow and store it for when demand needs it later. Electric Vehicles (EVs) have been discussed as a way of providing a distributed energy storage resource to the electric grid. However before EVs can be used to support the grid, through optimal charging and discharging, highly complex, non-linear driver behavior must be accounted for. In this work we combine machine learning with optimization to model driver behavior in order to size the capacity of energy storage EVs can offer the grid.