Pecan Street Announces the Vehicle-to-Grid University Challenge
Pecan Street is launching a global competition for university students to develop a robust Vehicle-to-Grid (V2G) control algorithm that optimizes residential fleets of electric vehicles for grid decarbonization and increased resiliency.
V2G technology allows power to flow from the grid to an electric vehicle when the car battery is charging, and vice-versa, from the vehicle back to the grid. This allows V2G-equipped electric vehicles to act in aggregate as mobile power plants and individually as local energy arbitrage systems, which can improve the efficiency and value of intermittent renewable energy like solar and wind.
Recent announcements, like California’s phase-out of gas vehicles by 2035, demonstrate clear policy and market momentum toward vehicle electrification. V2G technology creates cross-sector benefits and the opportunity for an integrated, smarter, and cleaner transportation and electric grid system. While the capability now exists within most EV’s to enable V2G services for the grid (and for customers to be paid for those services), scalable V2G management systems have yet to materialize.
Pecan Street seeks to accelerate the pace of this critical technology solution through a new university challenge in which students can compete for a $2,500 prize for the best V2G residential fleet management algorithm.
Competing teams will be given complimentary access to Pecan Street’s globally unique datasets on residential energy use, EV charging and PV generation as well as a simulation tool developed by Pecan Street’s engineers to test and refine their algorithms.
Pecan Street is one of the nation’s leading transportation electrification and V2G research organizations. With the installation at Pecan Street’s lab in 2018 of Texas first (and only) grid-connected V2G charging system combined with the EV charge data that Pecan Street has collected from hundreds of vehicles around the country for the past five years, competing students will have access to an unparalleled real-world testbed and a ground-truth simulation to unleash their innovation and creativity on solving this critical problem. Download our V2G case study to learn more about this project.
The V2G University Challenge is an invitation to the next generation of engineers to advance this pivotal research and to help make V2G technology a reality.
Teams interested in submitting challenge proposals will:
- Develop an algorithm designed for V2G system control and optimization for greatest overall grid benefit, i.e. managing the “duck curve” or afternoon peak.
- Demonstrate how the control and optimization algorithm would control connected devices and scale to large residential fleets of EVs.
- Preference will be given to submissions that include voltage and frequency control.
Pecan Street will grant access to a suite of residential energy use data (including EV charging) from 50 homes to be used by participating teams to demonstrate their algorithms. Data access will be granted to teams after registering.
Scoring Rubric & Prizes
The winners of the challenge will be awarded a $2,500 prize and be recognized before Pecan Street’s network of scientists and engineers, who work at universities, startups, and Fortune 500 companies. Pecan Street will select one winning team based on the scoring rubric below:
- Effectiveness of control and optimization capabilities of algorithm (50%)
- Device control capabilities (25%)
- Scalability of algorithm/system (25%)
- Extra Credit: Demonstrates voltage and frequency control (+15%)
- October 1, 2020: V2G Challenge announced – registration open
- October 31, 2020: Deadline to register participating teams
- November 13, 2020: Deadline to submit questions
- November 18, 2020: Official question responses posted publicly
- December 31, 2020: Final deadline for challenge submissions
- January 29, 2021: Challenge winners announced.
All currently enrolled university students are eligible to participate. Faculty members are not eligible to participate or assist in developing team submissions.