Right Place, Right Time (RiPiT) Carbon Emissions Service

The RiPiT project is researching, building, and deploying information services that digest the complex dynamics of power grids to enable computing to reduce its carbon emissions impact. The power grid is a complex, increasingly dynamic large-scale infrastructure with temporal and spatial variation in carbon-emission exceeding 10-times. As more renewables are deployed and grids are decarbonized, these ratios are increasing.

Computing's extraordinary agility (seconds, even milliseconds) provides a unique ability to respond and adapt, or plan and shift logistically to reduce carbon emissions. But to do so intelligently and productively, computing needs dynamic information that reflects the impact of power consumption. Computing also has a responsibility for climate change, as the cloud, high speed networking, and a growing universe of edge and client devices drive a rapidly growing consumption of power and carbon footprint.


Plan: RiPiT will provide a succession of information services and APIs that enable a variety of computing devices, systems, users to intelligently plan and execute compute load shifting in time and place, data and storage management, and battery charging. Such intelligent planning requires real-time and forecast data, but RiPiT faces several challenges to meet these needs.
  1. Most power grids do not provide sufficient and timely information, so RiPiT is exploring a range of analytic and inference techniques to provide guidance to computing systems. We expect this information to improve in accuracy, spatial and temporal resolution, and timeliness as the project progresses.
  2. Carbon emissions depend on the detailed temporal and geographic pattern of consumption, combined with the realized grid mix and dispatch. RiPiT will provide attribution services that allow consumption to be translated into carbon emission estimates.
  3. Efficient interaction with applications, and providing useful information in the presence of uncertainty is a difficult challenge. If you are interested in working with us to develop productive APIs, please contact us.

The RiPiT Metrics System includes several parts:

  • Part I: Examples of Grid Data and Metrics reported by real power grids (MISO, ERCOT, SWPP, CAISO) -- with varying definition, coverage, latency, and resolution. This highlights the challenge in "making sense" of data available in the power grid.
  • Part II: RiPiT-designed Metrics and Summaries that provide insights in thinking about how to reduce carbon emissions for computing. Grid behavior is distilled relative to workload properties (flexibility, temporal alignment, etc.) to suggest both where you might be able to achieve the largest reductions, and the likely difficulty of doing so. This provides a digested perspective on the complex dynamics of power grids. These new metrics are are computed from models, prediction, and grid provided data. They guide initial steps to find the most promising opportunities to reduce carbon emissions impact.
  • Part III: A RiPiT API that allows intelligent loads to express flexibility, evaluate potential carbon-emissions impact of load adaptation, register adaptation, and calculate impact. This is designed for applications to use the detailed workload structure and create intelligent management to reap reductions in carbon emissions, and document those reductions.

For background, see the : Zero Carbon Cloud (ZCCloud) Project which has demonstrated that

  1. Cloud computing is growing rapidly and consumes nearly 10 percent of grid power in several areas.
  2. To reduce its Scope 2 carbon emissions, one viable strategy is to adapt computing load spatially and temporally. Shifting should target when there are more renewables available, and also shift to increase the grids ability to absorb renewable generation.
  3. Shifting of datacenters loads of 10s to 100s of megawatts can be done effectively, eliminating carbon emissions and creating zero-carbon computing.


RiPiT is supported in part by a generous grant from VMWare Research and the National Science Foundation. RiPiT is part of the Zero-carbon cloud (ZCCloud) Project and the Large-scale Sustainable Systems Group (LSSG) at the University of Chicago .

People: Tristan Sharma, Varsha Rao, and Liuzixuan (Peter) Lin,  Andrew A. Chien (UChicago), Jiaqi Chen, Joseph Gorka, Line Roald, (U Wisconsin), and Rich Wolski (UCSB),  Former: Cameron Fiske, Fan Yang, Jeremy Archer (UChicago)