U.S. Department of EnergyOffice of Scientific and Technical Information
ARPA-E Grid Optimization (GO) Competition Challenge 1
Abstract
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, asmore »
- Publication Date:
- Other Number(s):
- 6153
- Research Org.:
- DOE Open Energy Data Initiative (OEDI); Pacific Northwest National Laboratory
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
- Collaborations:
- Pacific Northwest National Laboratory
- Subject:
- ACOPF; ARPA-E; Array; GO Competition; Unit Commitment; competition; computational science; data; energy; energy model; grid; grid optimization; model; optimal powerflow; optimization; power; security constrained; synthetic grid data
- OSTI Identifier:
- 2437761
- DOI:
- https://doi.org/10.25984/2437761
Citation Formats
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., 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. doi:https://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. doi:https://doi.org/10.25984/2437761. https://www.osti.gov/servlets/purl/2437761. Pub date:Mon Aug 05 00:00:00 EDT 2024
@article{osti_2437761,
title = {ARPA-E Grid Optimization (GO) Competition Challenge 1},
author = {Elbert, Stephen and Holzer, Jesse and Veeramany, Arun and Hedman, Kory and Mittelmann, Hans and Coffrin, Carleton and overbye, Thomas and Birchfield, Adam and DeMarco, Christopher and Duthu, Ray and Kuchar, Olga and Li, Hanyue and 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},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Aug 05 00:00:00 EDT 2024},
month = {Mon Aug 05 00:00:00 EDT 2024}
}