One of the primary challenges relating to the widespread electrification of transportation is the timing of electric vehicle (EV) charging. If all EV owners plug in their vehicles at the same time of day, electricity demand on the grid will rise suddenly and dramatically, forcing grid operators to quickly ramp up electricity production. Smart charging programs can help curb the detrimental side effects of a growing number of EVs simultaneously re-charging on the grid. These programs offer financial and other incentives to encourage consumers to shift their EV charging patterns to times of low electricity demand. Some of these smart charging programs incentivize consumers to allow companies to remotely control and manage their EV charging schedule through “vehicle-to-grid” (V2G) technology. This grant funds efforts to advance our understanding of the social, behavioral, and economic tradeoffs of different smart charging program features and assess how various program features might limit or facilitate a smart charging program’s viability, both nationally and in different regions and electricity grid systems. A research team led by John Helveston at The George Washington University and including Eric Hittinger (Rochester Institute of Technology), Alan Jenn (University of California, Davis), and Brian Tarroja (University of California, Irvine) will use a choice-based conjoint survey analysis to estimate how consumers value various smart charging program features. Program features that will be studied include how much consumers would need to be compensated for program participation, the time window a program would have control over vehicle charging, how much of the battery or percent of full charge the program has control over, and whether the program can determine when to charge the EV or when to discharge the vehicle back to the grid as part of a V2G program. The team will study these features both individually and in combination, gauging what mix of features would be most desirable for consumers. Results will be integrated into an energy systems model and used to investigate three case studies of smart charging programs in partnership with three utilities in different regions of the country to assess the real-world impacts of different program features on emissions reduction, peak electricity demand, and electric system costs. The team plans to produce at least two peer-reviewed journal articles, reports and policy briefs for practitioners, and will make survey data publicly available that facilitates integration with energy models for other researchers and utilities to use. Results are expected to help inform the design of future smart charging programs in different utility regions and for different consumer bases.