Background
Plug-in electric vehicle (PEV) usage is expected to have a major impact on energy sources, grid loads and local emissions of the facility used as the charging origin and destination of those vehicles. The first direct impact of both battery electric vehicles (BEVs) and plug in electric vehicles (PHEVs) is electric charging loads. Light duty vehicles may have low demand per vehicle, but large numbers of fleet or commuter vehicles may create local loads on the distribution network. Other transportation services such as transit and heavy duty vehicles may be less flexible in charging needs but also have the potential for Vehicle Grid Integration and serve as emergency backup if needed. The spatial and temporal patterns of the grid loads are an outcome of technology adoption and usage. For example, a fleet of PHEVs can be used mostly as fully electric cars if charged frequently at the beginning and end of trips and can also be used for balancing loads using the internal combustion engine if needed. A smart grid connected to the facility’s load management system may control and prioritize vehicle charging by type usage or presentiment decision rules.
Project Goals
- Use and combine existing datasets and datasets collected by other Center projects to create and improve analysis tools for PEV usage and EV infrastructure location and usage in order to optimize the impact of different vehicle models, infrastructure scenarios and policies in a given base/location/area.
- Package the analysis tools in a toolbox that can be used in similar facilities and army bases with minimum modification.
Principal Investigator: Gil Tal
Additional Staff: Dahlia Garas, Ken Kurani
Undergraduate Students: Scott Begneski (military), Eric Racadag (military), Alex Tang (military)
Graduate Students: Alex Campbell (military)
