Easily Accessible and Usable Datasets for Grid Management Innovation
ARPA-E’s Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program seeks to develop new grid management systems that represent the relative delivery risk of individual electricity generation resources and balance the collective risk of all assets across the grid. The program has funded twelve project teams across the country to build software platforms that optimize grid management as the penetration of variable renewable resources continues to increase. However, the difficulty of obtaining and sharing sensitive transmission grid data has historically presented a challenge for innovation.
To overcome this challenge, PERFORM also funded leading power systems modelling groups at Lawrence Livermore National Laboratory, National Renewable Energy Laboratory, Princeton University, Texas A&M University, and the University of Wisconsin to generate realistic synthetic datasets for the power grid. These datasets served as a basis for the twelve optimization teams to develop their platforms.
The dataset teams have now come together to make their data publicly available via the links below. Each unique dataset can be used for a variety of applications specified by each respective team. ARPA-E hopes that making this data widely accessible will spur additional innovation in grid management beyond the PERFORM program.
For questions regarding the PERFORM Program, please contact Technology-to-Market Advisor Jonathan Glass (jonathan.glass@hq.doe.gov)
PEFORM Cases are listed here:
- Texas A&M University
- Lawrence Livermore National Laboratory
- National Renewable Energy Laboratory
- Princeton University
- University of Wisconsin-Madison
For questions regarding the PERFORM Cases, please contact:
- Texas A&M grid models: Farnaz Safdarian (fsafdarian@tamu.edu)
- LLNL system: Jean-Paul Watson (watson61@llnl.gov)
- NREL datasets: Brian Sergi (bsergi@nrel.gov)
- Princeton data plan: René A. Carmona (rcarmona@princeton.edu)
- University of Wisconsin-Madison cases: Scott Greene (sgreene1@wisc.edu)