ARPA-E Grid Optimization (GO) Competition Challenge 3
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.
Challenge 1 and Challenge 2 information can be found in the resources linked below.
Citation Formats
Pacific Northwest National Laboratory. (2024). ARPA-E Grid Optimization (GO) Competition Challenge 3 [data set]. Retrieved from https://dx.doi.org/10.25984/2426334.
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. doi: 10.25984/2426334.
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://dx.doi.org/10.25984/2426334
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://dx.doi.org/10.25984/2426334. 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.
Challenge 1 and Challenge 2 information can be found in the resources linked below. }, doi = {10.25984/2426334}, url = {https://data.openei.org/submissions/5997}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {05}}
https://dx.doi.org/10.25984/2426334
Details
Data from May 2, 2024
Last updated Sep 27, 2024
Submitted May 2, 2024
Organization
Pacific Northwest National Laboratory
Contact
Stephen Elbert
619.813.4210
Authors
Research Areas
Keywords
energy, power, ACOPF, Unit Commitment, multiperiod, GO Competition, security-constrained optimal power flow, grid, grid optimization, ARPA-E, competition, computational science, model, multiperiod dynamic markets, energy model, optimization, challenge 3DOE Project Details
Project Name ARPA-E Grid Optimization Competition
Project Number CJ0000903
