U.S. Energy Secretary Dan Brouillette announced that the first round of winners has been named in the Department of Energy’s Grid Optimization (GO) Competition. The GO Competition, managed by DOE’s Advanced Research Projects Agency-Energy (ARPA‑E) is a series of challenges to develop software management solutions for challenging power grid problems. The competition’s intent is to create a more reliable, resilient and secure American electricity grid. The winners will share a total of $3.4 million, which is to be used to further develop their respective approaches and pursue industry adoption of their technologies.
Richard O'Neill took over as the ARPA-E Program Director of the Grid Optimization (GO) Competition today. He served as the Chief Economic Advisor at the Federal Energy Regulatory Commission (FERC) before coming to ARPA-E.
The GO Competition Platform will lock-down its software environment on September 2, 2019 and will remain locked for the duration of the Challenge 1 competition. Competition teams should submit any requests for changes before that date to the GO Competition Administrator.
The GO Competition will now host a third trial event designed to give teams more opportunities to work with large datasets similar to those from Trial Event 2. Trial Event 3 will test a smaller number of scenarios than Trial Event 2 and is optional, but all teams are encouraged to participate.
In order to maximize the development time for the competitors, with open access to the sandbox for testing, we will shorten the submission window from fourteen days to three days and slightly reschedule the Trial 2 Event to the end of the work week. The new Trial 2 submission window will be from July 17th – July 19th.
Challenge 1 - Trial Event 1 is open from April 1 00:00 PDT until April 15 23:59 PDT; no prizes are associated with this event. Both the Sandbox and other Challenge 1 datasets will remain open and available during this time.
Each team is allowed only one submission for this event. Teams can submit to Trial Event 1 by submitting a Challenge 1 submission and selecting the Trial Event 1 dataset. Good luck!
A webinar with the topic "Challenge 1 Overview and Registration" was held at 12:00 pm ET. The webinar recording is available on YouTube. The webinar slides are available for download. Additional information may be found on the Registration page.
Secretary of Energy Rick Perry today announced ARPA-E's first ever Grid Optimization (GO) Competition. The GO Competition is a series of challenges to develop software management solutions for a resilient and secure American electricity grid. Today marks the beginning of GO Challenge 1, offering up to $4 million in prizes to develop new algorithms to make routing power across the grid faster and more efficient. See Press Release.
Daniel S. Kheloussi, Energy Industry Analyst, Federal Energy Regulatory Commission (FERC) sent an e-mail to people registered for FERC's Ninth Annual Software Conference - June 26-28, 2018 informing them of the ARPA-E GRID OPTIMIZATION COMPETITION WORKSHOP 1:15PM to 3:30PM on June 28, 2018. View the announcement from FERC, and download the workshop details included as attachments (PDF, MSWord).
ARPA-E held a 90 minute webinar to directly involve the community, via a Request for Information (RFI), on the design of this competition. The RFI was released October 11, 2016. View a video recording of the webinar.
ARPA-E announced $11 million in funding for seven transformational projects as part of ARPA-E’s newest program, Generating Realistic Information for the Development of Distribution and Transmission Algorithms (GRID DATA).GRID DATA Program awards announced. View the GRID DATA Program announcement; view the GRID DATA projects.
ARPA-E issues Generating Realistic Information for the Development of Distribution and Transmission Algorithms (GRID DATA) Funding Opportunity Annoucement (FOA). One of the objectives is that "models and repository created in this program may be used as the basis for an ARPA-E OPF algorithm competition." View the FOA (DE-FOA-0001357) pdf.