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.

This grant provides ongoing support to the Open Energy Outlook (OEO) Initiative, a multi-disciplinary, open-source, publicly available energy system model collaboration led by scholars at Carnegie Mellon University and North Carolina State University. The OEO Initiative involves input from over 40 consulting external subject matter experts from fields such as policy, electricity, buildings, and transportation, and it provides an open-source platform that makes energy system analysis more accessible to a range of stakeholders and applicable to different geographies and sectors. Grant funds will provide the organizational resources necessary to help grow and sustain the OEO Initiative over the coming years, involving three primary tasks. First, the team will update the open-source modeling platform that the OEO Initiative is based on, called the Tools for Energy Model Optimization and Analysis (Temoa) model, to better represent recent energy policy developments and legislation. Second, the team will develop a strategic plan that charts the longer-term path for their research, fundraising, and operational model, which includes establishing a consortium of funding partners from industry, nonprofits, and other foundations. Finally, the team will participate in research partnerships that will apply and extend the OEO Initiative framework to specific states, sectors, and other regions and countries. These research partnership efforts are expected to train 4-6 graduate students at a variety of institutions deploying the Temoa model. Funds will primarily go towards supporting the Executive Director role in managing the OEO Initiative.