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ARPA-E Grid Optimization (GO) Competition Challenge 3

Publicly accessible License 

Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public.

The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead.

In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023).

For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below.

Citation Formats

Pacific Northwest National Laboratory. (2024). ARPA-E Grid Optimization (GO) Competition Challenge 3 [data set]. Retrieved from https://data.openei.org/submissions/5997.
Export Citation to RIS
Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, O'Neill, Richard, Mittelmann, Hans, Coffrin, Carleton, Garcia, Manuel, Parker, Robert, Elgindy, Tarek, Hale, Elaine, Palmintier, Bryan, Mak, Terrence, Overbye, Thomas, Safdarian, Farnaz, DeMarco, Christopher, Greene, Scott, Lesieutre, Bernard, Eldridge, Brent, and Oh, Hyungseon. ARPA-E Grid Optimization (GO) Competition Challenge 3. United States: N.p., 02 May, 2024. Web. https://data.openei.org/submissions/5997.
Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, O'Neill, Richard, Mittelmann, Hans, Coffrin, Carleton, Garcia, Manuel, Parker, Robert, Elgindy, Tarek, Hale, Elaine, Palmintier, Bryan, Mak, Terrence, Overbye, Thomas, Safdarian, Farnaz, DeMarco, Christopher, Greene, Scott, Lesieutre, Bernard, Eldridge, Brent, & Oh, Hyungseon. ARPA-E Grid Optimization (GO) Competition Challenge 3. United States. https://data.openei.org/submissions/5997
Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, O'Neill, Richard, Mittelmann, Hans, Coffrin, Carleton, Garcia, Manuel, Parker, Robert, Elgindy, Tarek, Hale, Elaine, Palmintier, Bryan, Mak, Terrence, Overbye, Thomas, Safdarian, Farnaz, DeMarco, Christopher, Greene, Scott, Lesieutre, Bernard, Eldridge, Brent, and Oh, Hyungseon. 2024. "ARPA-E Grid Optimization (GO) Competition Challenge 3". United States. https://data.openei.org/submissions/5997.
@div{oedi_5997, title = {ARPA-E Grid Optimization (GO) Competition Challenge 3}, author = {Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, O'Neill, Richard, Mittelmann, Hans, Coffrin, Carleton, Garcia, Manuel, Parker, Robert, Elgindy, Tarek, Hale, Elaine, Palmintier, Bryan, Mak, Terrence, Overbye, Thomas, Safdarian, Farnaz, DeMarco, Christopher, Greene, Scott, Lesieutre, Bernard, Eldridge, Brent, and Oh, Hyungseon.}, abstractNote = {Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public.

The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead.

In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023).

For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below. }, doi = {}, url = {https://data.openei.org/submissions/5997}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {05}}

Details

Data from May 2, 2024

Last updated May 14, 2024

Submitted May 2, 2024

Organization

Pacific Northwest National Laboratory

Contact

Stephen Elbert

619.813.4210

Authors

Stephen Elbert

Pacific Northwest National Laboratory

Jesse Holzer

Pacific Northwest National Laboratory

Arun Veeramany

Pacific Northwest National Laboratory

Richard O'Neill

U.S. Department of Energy Advanced Research Projects Agency-En...

Hans Mittelmann

Arizona State University

Carleton Coffrin

Los Alamos National Laboratory

Manuel Garcia

Los Alamos National Laboratory

Robert Parker

Los Alamos National Laboratory

Tarek Elgindy

National Renewable Energy Laboratory

Elaine Hale

National Renewable Energy Laboratory

Bryan Palmintier

National Renewable Energy Laboratory

Terrence Mak

Monash University

Thomas Overbye

Texas AM University

Farnaz Safdarian

Texas AM University

Christopher DeMarco

University of Wisconsin-Madison

Scott Greene

University of Wisconsin-Madison

Bernard Lesieutre

University of Wisconsin-Madison

Brent Eldridge

Pacific Northwest National Laboratory

Hyungseon Oh

Booz Allen and Hamilton contractor to ARPA-E

DOE Project Details

Project Name ARPA-E Grid Optimization Competition

Project Number CJ0000903

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