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ARPA-E Grid Optimization (GO) Competition Challenge 1

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The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each dataset consisted of a collection of power system network models of different sizes with associated operating scenarios (snapshots in time defining instantaneous power demand, renewable generation, generator and line availability, etc.). The datasets were of two types: Real-Time, which included starting-point information, and Online, which did not. Week-Ahead data is also provided for some cases but was not used in the Competition. Although most datasets were synthetic and generated by GRIDDATA, a few came from industry and were only used in the Final Event. All synthetic Input Data and Team Results for the GO Competition Challenge 1 for the Sandbox, Trial Events 1 to 3, and the Final Event along with problem, format, scoring and rules descriptions are available here. Data for industry scenarios will not be made public.

Challenge 1, a minimization problem, required two computational steps. Solver 1 or Code 1 solved the base SCOPF problem under a strict wall clock time limit, as would be the case in industry, and reported the base case operating point as output, which was used to compute the Objective Function value that was used as the scenario score. The feasibility of the solution was provided by the Solver 2 or Code 2, which solves the power flow problem for all contingencies based on the results from Solver 1. This is not normally done in industry, so the time limits were relaxed. In fact, there were no time limits for Trial Event 1. This proved to be a mistake, with some codes running for more than 90 hours, and a time limit of 2 seconds per contingency was imposed for all other events. Entrants were free to use their own Solver 2 or use an open-source version provided by the Competition.

Containers, such as Docker, were considered to improve the portability of codes, but none that could reliably support a multi-node parallel computing environment, e.g., MPI, could be found.

For more information on the competition and challenge see the "GO Competition Challenge 1 Information" and "GO Competition Challenge 1 Additional Information" resources below.

Citation Formats

Pacific Northwest National Laboratory. (2024). ARPA-E Grid Optimization (GO) Competition Challenge 1 [data set]. Retrieved from https://dx.doi.org/10.25984/2437761.
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Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, Hedman, Kory, Mittelmann, Hans, Coffrin, Carleton, Overbye, Thomas, Birchfield, Adam, DeMarco, Christopher, Duthu, Ray, Kuchar, Olga, Li, Hanyue, Tbaileh, Ahmad, and Wert, Jessica. ARPA-E Grid Optimization (GO) Competition Challenge 1. United States: N.p., 05 Aug, 2024. Web. doi: 10.25984/2437761.
Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, Hedman, Kory, Mittelmann, Hans, Coffrin, Carleton, Overbye, Thomas, Birchfield, Adam, DeMarco, Christopher, Duthu, Ray, Kuchar, Olga, Li, Hanyue, Tbaileh, Ahmad, & Wert, Jessica. ARPA-E Grid Optimization (GO) Competition Challenge 1. United States. https://dx.doi.org/10.25984/2437761
Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, Hedman, Kory, Mittelmann, Hans, Coffrin, Carleton, Overbye, Thomas, Birchfield, Adam, DeMarco, Christopher, Duthu, Ray, Kuchar, Olga, Li, Hanyue, Tbaileh, Ahmad, and Wert, Jessica. 2024. "ARPA-E Grid Optimization (GO) Competition Challenge 1". United States. https://dx.doi.org/10.25984/2437761. https://data.openei.org/submissions/6153.
@div{oedi_6153, title = {ARPA-E Grid Optimization (GO) Competition Challenge 1}, author = {Elbert, Stephen, Holzer, Jesse, Veeramany, Arun, Hedman, Kory, Mittelmann, Hans, Coffrin, Carleton, Overbye, Thomas, Birchfield, Adam, DeMarco, Christopher, Duthu, Ray, Kuchar, Olga, Li, Hanyue, Tbaileh, Ahmad, and Wert, Jessica.}, abstractNote = {The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each dataset consisted of a collection of power system network models of different sizes with associated operating scenarios (snapshots in time defining instantaneous power demand, renewable generation, generator and line availability, etc.). The datasets were of two types: Real-Time, which included starting-point information, and Online, which did not. Week-Ahead data is also provided for some cases but was not used in the Competition. Although most datasets were synthetic and generated by GRIDDATA, a few came from industry and were only used in the Final Event. All synthetic Input Data and Team Results for the GO Competition Challenge 1 for the Sandbox, Trial Events 1 to 3, and the Final Event along with problem, format, scoring and rules descriptions are available here. Data for industry scenarios will not be made public.

Challenge 1, a minimization problem, required two computational steps. Solver 1 or Code 1 solved the base SCOPF problem under a strict wall clock time limit, as would be the case in industry, and reported the base case operating point as output, which was used to compute the Objective Function value that was used as the scenario score. The feasibility of the solution was provided by the Solver 2 or Code 2, which solves the power flow problem for all contingencies based on the results from Solver 1. This is not normally done in industry, so the time limits were relaxed. In fact, there were no time limits for Trial Event 1. This proved to be a mistake, with some codes running for more than 90 hours, and a time limit of 2 seconds per contingency was imposed for all other events. Entrants were free to use their own Solver 2 or use an open-source version provided by the Competition.

Containers, such as Docker, were considered to improve the portability of codes, but none that could reliably support a multi-node parallel computing environment, e.g., MPI, could be found.

For more information on the competition and challenge see the "GO Competition Challenge 1 Information" and "GO Competition Challenge 1 Additional Information" resources below.
}, doi = {10.25984/2437761}, url = {https://data.openei.org/submissions/6153}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {08}}
https://dx.doi.org/10.25984/2437761

Details

Data from Aug 5, 2024

Last updated Sep 27, 2024

Submitted Aug 5, 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

Kory Hedman

Arizona State University

Hans Mittelmann

Arizona State University

Carleton Coffrin

Los Alamos National Laboratory

Thomas Overbye

Texas AM University

Adam Birchfield

Texas AM University

Christopher DeMarco

University of Wisconsin - Madison

Ray Duthu

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

Olga Kuchar

Oak Ridge National Laboratory

Hanyue Li

Texas AM University

Ahmad Tbaileh

Pacific Northwest National Laboratory

Jessica Wert

Texas AM University

DOE Project Details

Project Name ARPA-E Grid Optimization Competition

Project Number CJ0000903

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