12. Learning and control for decarbonized energy and transportation systems
Organizers: Sivaranjani Seetharaman and Apurv Shukla
Location: Roselle Junior 4613
Website: https://sites.google.com/tamu.edu/cdc-2023-workshop/home
Abstract: Climate change is the most pressing problem facing humanity in the coming decades. To address this challenge, there are significant efforts underway at the international level towards decarbonization of our critical societal infrastructures. A critical pathway in this regard is joint decarbonization of the electricity and transportation sectors, which are the two largest contributors to emissions worldwide (at nearly 25% and 29% of total GHG emissions, respectively.) The Control for Societal-scale Challenges: Road Map 2030 from the IEEE Control Systems Society also identifies climate change and resilient infrastructures as key areas that require research advances led by the control community. From an engineering perspective, accomplishing decarbonized energy and transportation requires large-scale integration of electrified mobility, renewables, distributed energy resources (DERs), storage, and alternative fuels like hydrogen. However, this transition poses serious operational challenges in terms of grid stability and resilience due to uncertain loads like electric vehicles being served by volatile sources like renewable generation. These reliability challenges are only expected to be further compounded due to climate change induced extreme events. Thus, safe, optimal and reliable operation of decarbonized energy-transportation infrastructures will require advances at the intersection of control, optimization, and machine learning at every stage.
We have an exciting slate of experts on this topic. The confirmed talks will cover a wide range of advances including new control strategies for the optimal and safe operation of renewable-rich grids, co-optimization algorithms for management of EVs, heavy-duty, and hydrogen-fueled vehicles, learning-based control and optimization of DERs for demand response at the grid edge, and market/incentive designs for safe operation at the transportation-energy nexus.