Lei Fan
University of Houston, TX·Engineering·Early-career
Hyperscale data centers are becoming some of the largest electricity consumers on the grid, and their demand is growing fast. Unlike a factory or a household, a data center has unusual freedom: it can shift computing jobs to a later hour or to a facility in another region, which means its power draw is partly adjustable.
- Fields
Engineering
Mathematics & Statistics
Computer Science
- Topics
power systems
data centers
demand flexibility
- Grants
- 1 known grant, through Apr 2031
What they work on
- Develop mixed-integer linear and convex optimization models that capture how data center computing load can shift across time and location, embedded within security-constrained unit commitment for scheduling generators under network limits.
- Build hybrid quantum-classical optimization frameworks that place quantum subroutines based on quantum dynamics inside classical decomposition methods, so that large-scale grid and data center co-optimization problems become tractable.
- Design adaptive quantum evolution techniques that optimize Hamiltonian scheduling, the time recipe governing the quantum system, to improve convergence speed and robustness of the quantum optimization subroutines.
- Address co-optimization of power system operations and data center flexibility under uncertainty in demand and supply, overcoming limitations of existing classical solution methods for these large problems.
More about the research
This project asks how grid operators and data centers can coordinate so that this flexibility helps keep electricity reliable and affordable rather than straining the system, and it pursues the question using both conventional optimization and quantum computing.
Why it matters
Electricity demand from large data centers is expected to grow sharply over the coming decade, raising concerns about grid reliability and consumer costs. Tools that let data centers shift when and where they consume power, coordinated with generator scheduling, could support cheaper and more reliable grid operation and help energy-efficient data centers be sited and run across the United States.
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.
Monika Filipovska
University of Connecticut, CT·Engineering
Develop quantum simulation algorithms that encode spatial and temporal dependencies of stochastic transportation networks into quantum states, using quantum amplitude estimation and dimensionality reduction to improve efficiency.
Illya Hicks
Rice University, TX·Mathematics & Statistics
Develop polyhedral theory — representing discrete choices as geometric shapes amenable to linear methods — to formulate and solve optimization problems for battery storage in microgrids.
The school
University of Houston: 21 labs on PI Pages, $239M a year on research, 374 research doctorates a year.
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