New research into decarbonisation of the transport sector through EV ride-share

If you’re standing on a corner waiting for a ride-share car, would you be willing to wait longer if you knew your driver was driving an electric vehicle? What if it was powered by 100% green energy? How long would you be willing to wait? Would you pay more for the privilege if the app told you the alternative?

recently submitted a paper scientific report (and available at arXiv preprint server) from researchers in the Department of Electrical, Computer and Energy Engineering at CU Boulder explores those questions as part of a larger push globally to decarbonize transportation services.

First author and postdoctoral researcher Elisabetta Perotti said the paper considers a scenario in which a 100% electrified fleet of vehicles is powered by both ride requests submitted by customers and charging requests sent by the utility company during periods of high renewable energy production. should be involved.

“For example, a ride-hailing company like Lyft receives both of these types of requests and then has to solve an optimization problem to decide how best to allocate available electric vehicles to minimize operating costs. It is,” Perotti said. “In this paper we propose incentives to promote the charging of electric vehicles during hours of high renewable generation and balance that against quality of service and the public’s willingness to use the system.”

Perotti said better synchronization with a schedule that prioritizes renewable energy sources would avoid negative impacts on the grid that could come from uncontrolled charging schedules for fleets.

Perotti is working in this area through a Schmidt Science Fellowship. The typical program combines postdoctoral research in engineering, natural science, mathematics, or computing with a discipline that differs from the individual’s current area of ​​expertise and planned area of ​​future research. Perotti already has his Ph.D. He had a strong background in theoretical physics and mathematics. at Uppsala University in Sweden and said she is using the fellowship to focus on concrete problems in renewable energy.

“I knew that many researchers at CU Boulder are working on ambitious plans to combat climate change and that the university has become an example for the whole of America in leading the way in energy transition,” she said. “It quickly became clear that[Emiliano Dall’Anese’s lab]would be a good fit for me because it would allow me to combine my passion for mathematics with the concrete purpose of addressing environmental and climate change concerns.” Is.”

The paper outlines a mechanism inspired by game theory in which the power utility company proposes an incentive and then the ride-sharing platform provides vehicles for both the ride and the charge request. To test their work, the team used sample data recorded by the Taxi and Limousine Commission in New York City and renewable energy information from the New York Independent System Operator.

The results suggest that it is possible to shift the charging of electric vehicles to overlap with periods of high renewable generation and for ride-sharing platforms to adapt to intermittent power generation while minimizing the impact on service quality.

Developing the core algorithm for this task was not easy, according to Perotti, who worked with researchers from Belgium’s Catholic University of Louvain and the Polytechnique Institute of Paris on the project.

“The ride-service provider and the utility company have different objectives, so it is challenging to formulate an optimization problem that aims to minimize both their operating costs,” she said. “It becomes even more complex when financial incentives and our bargaining mechanisms are included in the ‘game’, so there is a lot to consider and manage algorithmically.”

Perotti said the paper also shows that some form of ridesharing is necessary in the future to fully benefit from the active fleet of electric vehicles powered by renewable energy such as wind and solar.

Perotti said he has had the opportunity to work with Associate Professor Emiliano Dall’Anese and gain exposure, skills and knowledge with optimization and control theory in his group.

“Even though my PhD research was theory-based, I learned how to operate combined a broad toolbox of mathematics, physics, computer science and problem-solving techniques,” she said. “Those interdisciplinary skills are proving useful in this research area and will be useful for years to come as I apply them to my pivot research that addresses global challenges.”