Subhonmesh Bose
University of Illinois Urbana-Champaign, IL·Engineering·Early-career
How can a decision-maker steer others toward good outcomes when the future is uncertain or the others act on their own interests? Both questions matter for the electric grid.
- Fields
Engineering
Mathematics & Statistics
Computer Science
- Topics
incentive design
electricity markets
power systems
- Grants
- 2 known grants, through Aug 2027
What they work on
- Determine whether agents can learn each other's preferences through repeated interactions in incentive design problems, using tools from game theory, control theory and machine learning.
- Analyze how behavioral traits from behavioral economics shape incentive structures, and design incentives for complex hierarchies of interacting agents, applied to coordinating distributed energy resources.
- Develop risk-sensitive electricity market clearing formulations that balance reactive and conservative responses to wind and solar uncertainty, along with efficient algorithms to solve them.
- Design pricing for electricity market participants from risk-sensitive formulations, and create methods that combine historical measurements with simulated data in decision-making.
More about the research
Wind and solar power vary in ways no one controls, and many small energy devices must be coordinated without direct command. The lab tackles these problems with mathematics drawn from optimization, control theory, game theory and machine learning. One project designs incentives that induce desired behavior. The other redesigns electricity markets to handle renewable uncertainty.
Why it matters
Grid operators must integrate more wind and solar power and coordinate many distributed energy resources. Risk-sensitive electricity markets and pricing could help them handle uncertain supply without wasteful over-caution. Practical incentive designs could also inform environmental policy and the structure of organizations.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Bing Yan
Rochester Institute of Technology, NY·Engineering·Early-career
Build market participation models for energy storage resources that range from self-scheduling to full operator management, accounting for changing state-of-charge limits and uncertain renewable output.
Jan Kleissl
University of California-San Diego, CA·Engineering
Build DERConnect, a remote-access testbed that integrates solar panels, battery storage, electric vehicles, wind and solar emulators, and controllable building lighting and HVAC (heating, ventilation and air conditioning) systems.
Mingxi Liu
University of Utah, UT·Engineering·Early-career
Develop optimization, machine learning and statistical tools for a grid-edge resource control framework that scales with device population and network size and works across different device types and grid services.
The school
University of Illinois Urbana-Champaign: 41 labs on PI Pages, $907M a year on research, 870 research doctorates a year.
Reach out
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