CNS: Core: Small: Energy and Load Management in Data Centers: Online Optimization and Learning

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

Data centers, the backbone of the internet, are using increasingly massive amounts of power, consuming by some estimates up to 3% of the world's power supply and doubling their appetite every four years. This increasing appetite for power has significant ramifications for both costs -- electricity counts among the largest expenses in operating a data center -- and unwelcome contributions to climate change. Major data centers are working to meet this challenge by creating their own renewable energy sources (such as wind and solar farms) and energy storage systems in addition to the electric grid. But the fluctuation and lack of reliability built into the supply of energy from renewable sources causes significant challenges for data centers attempting to efficiently procure energy from these sources in combination with the grid. This project aims to use proven methods of algorithms and machine learning to optimize the energy procurement and load management of data centers under these challenges. In doing so, it will enable data centers to minimize their energy costs, maximize robustness against uncertainty, and improve their energy footprints. As a result, the successful implementation of this project will have a significant impact on lowering the overall cost of internet services. More broadly, by modeling how to more efficiently use renewable sources and energy storage systems, this research has significance beyond data centers. This project will facilitate the efficient and reliable incorporation of renewables into the operations of other large energy customers, playing a key role in moving toward a greener and more sustainable electric grid. The project will broaden participation by involving undergraduates in the research and will include outreach activities on introducing data centers to local K-12 students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.