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ARPA-E Grid Optimization (GO) Competition Challenge 2
The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment. Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. Specifically, the economic surplus, defined as the benefit of serving load minus the cost of generation, is being maximized. It was expected that the objective value of a given solution should be positive, representing economic gain, but negative objectives from poor solutions were possible. The two code submission feature of Challenge 1 was maintained. Additionally, Divisions 3 and 4 within the competition permitted on/off switching of transmission lines (Divisions 1 and 2 did not).
After the initial release of the Problem Formulation on 7/20/2020, ARPA-E Director Lane Genatowski announced Challenge 2 on 9/12/2020. The final May 31, 2021, version of the Problem Formulation was 97 pages long with 299 equations. The Challenge proceeded with 2 non-prize Events and 2 prize Events. Teams receiving Challenge 1 FOA awards and prize money were required to use the prize money to fund their Challenge 2 efforts (Georgia Institute of Technology, Global Optimal Technology, Inc., Lawrence Livermore National Laboratory, Lehigh University, Northwestern University, Artelys, Columbia, Pearl Street Technologies, Pennsylvania State University, and University of Colorado Boulder).
For more information on the competition and challenge 2 see the "GO Competition Challenge 2 Information" resource below.
Challenge 1 and Challenge 3 information can be found in the resources linked below.
Resources
29 resources available
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ARPA-E Grid Optimization GO Competition Challenge 3
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ARPA-E Grid Optimization GO Competition Challenge 1
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GO Competition Final Report
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GO Competition Challenge 2 Information
HTML -
Challenge 2 C2FEN17700 Unused Synthetic Scenarios.zip
ZIP -
Challenge 2 C2FEN08300 Unused Synthetic Scenarios.zip
ZIP -
Challenge 2 C2FEN31777 Unused Synthetic Scenarios.zip
ZIP -
Challenge 2 Wisconsin Data Narratives.zip
ZIP -
Challenge 2 Sandbox Data C2S7 Scenarios.zip
ZIP -
Challenge 2 C2FEN12209 Unused Synthetic Scenarios.zip
ZIP -
Challenge 2 Sandbox Data C2S6 Scenarios.zip
ZIP -
GO Competition Additional Info.pdf
PDF -
Challenge 2 Monarch of the Mountain Results.xlsx
XLSX -
Challenge 2 Trial Event 3 Results.xlsx
XLSX -
Challenge 2 Final Event Results.xlsx
XLSX -
Challenge 2 Problem Formulation.pdf
PDF -
Challenge 2 Sandbox Data C2S9 Scenarios.zip
ZIP -
Challenge 2 Additional Info.pdf
PDF -
Challenge 2 C2FEN0xxxx Unused Synthetic Scenarios.zip
ZIP -
Challenge 2 C2FEN1xxxx Unused Synthetic Scenarios.zip
ZIP -
Challenge 2 Sandbox Data C2S6N00617 Scenarios.zip
ZIP -
Challenge 2 Event 3 Synthetic Data Scenarios.zip
ZIP -
Challenge 2 Trial Event 1 Synthetic Data Scenarios.zip
ZIP -
Challenge 2 Trial Event 2 Synthetic Data Scenarios.zip
ZIP -
Challenge 2 Final Event 4 Synthetic Data Scenarios.zip
ZIP -
Challenge 2 Rules.pdf
PDF -
Challenge 2 Scoring.pdf
PDF -
Challenge 2 Timeline.pdf
PDF -
Challenge 2 Trial Event 2 Results.xlsx
XLSX
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| description | The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment. Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. Specifically, the economic surplus, defined as the benefit of serving load minus the cost of generation, is being maximized. It was expected that the objective value of a given solution should be positive, representing economic gain, but negative objectives from poor solutions were possible. The two code submission feature of Challenge 1 was maintained. Additionally, Divisions 3 and 4 within the competition permitted on/off switching of transmission lines (Divisions 1 and 2 did not). After the initial release of the Problem Formulation on 7/20/2020, ARPA-E Director Lane Genatowski announced Challenge 2 on 9/12/2020. The final May 31, 2021, version of the Problem Formulation was 97 pages long with 299 equations. The Challenge proceeded with 2 non-prize Events and 2 prize Events. Teams receiving Challenge 1 FOA awards and prize money were required to use the prize money to fund their Challenge 2 efforts (Georgia Institute of Technology, Global Optimal Technology, Inc., Lawrence Livermore National Laboratory, Lehigh University, Northwestern University, Artelys, Columbia, Pearl Street Technologies, Pennsylvania State University, and University of Colorado Boulder). For more information on the competition and challenge 2 see the "GO Competition Challenge 2 Information" resource below. Challenge 1 and Challenge 3 information can be found in the resources linked below. |
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"description": "Supporting ARPA-E Power Grid Optimization (Final Report)"
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"description": "The link has a description of Grid Optimization (GO) Competition Challenge 2, Problem Formulation, Datasets, Input Files and Format, Output Files and Format, Submissions, Solution Evaluation, Scoring, Timeline, Rules, and Leaderboards (the full list of competing teams and prizes)."
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"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Wisconsin_Data_Narratives.zip"
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"description": "80 scenarios from 16 network models (617-, 793-, 2020-, 2312-, 4102-, 4230-, 5752-, 6473, 8032-, 9459-, 9460-, 9462-, 12209-, 14212-, 24465-, and 31777-buses) published March 5, 2021. Scenarios with a negative market surplus for the prior operating point, MSpp or zpp (defined in section D.2 of the Problem Formulation) are possible and generally reflect high penalties imposed on the solution by a poor prior operating point. The GO Competition did not use such scenarios in any Trial or Final Events. There were, however, 3 such scenarios in C2S7, specifically, C2S7N12209 scenario 4 (-16,673,022) and scenario 8 (-99,958) and C2S7N14212 scenario 3 (-13,205,325,795). The first two are the result of legitimate, but poor, prior operating points. The later, however, was the result of an error in constructing the data that resulted in a bad power balance. This scenario was replaced (but not published) with one with a zpp value of 7,610,313. The only difference between the new scenario and the old is better values in the raw file for the VM and VA parameters in the Bus Data block and PG and QG parameters in the Generator Data block. The new scenario replaces C2S7N14212 scenario 3 for Sandbox submissions after March 12, 2021.",
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"description": "91 12,209-bus network scenarios developed for Challenge 2 Final Event but never used. ",
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"description": "A set of 12 network models (14-, 594-, 2000-, 2045-, 2380-, 2742-, 4226-, 4230-, 9459-, 9460-, 9462-, and 11152-buses) consisting of a total of 38 scenarios. Details are in C2S6_details.csv. ",
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"title": "GO Competition Additional Info.pdf",
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"description": "Additional information about the ARPA-E Power Grid Optimization project.",
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"description": "At the conclusion of Challenge 2, and while Challenge 3 was being developed in 2022, the public were invited to register and see if they could produce better solutions to the 84 synthetic Challenge 2 Final Event (4) datasets with no restrictions on time, hardware, or algorithms. Submissions, which consisted of the appropriate solution files and evaluation.py (Eval) output, were opened on January 3, 2022, and the results, confirmed at PNNL, were updated every Wednesday until 11/1/2022. Two teams were awarded a total of $440,000: $430,000 to GravityX and $10,000 to Gordian Knot. Prizes were given for the best improvement over 1% and for the longest time with the best result on the leaderboard (to discourage withholding results until the last moment). Six teams made a total of 201 submissions. GOT-BSI-OPF had 8 best results but were on the Leaderboard less time than GravityX so they received no prize. Improved results were found for all 84 datasets with improvements running from 6.7% to 0.00039%. There were 4 scenarios with improvements >1%, all found by GravityX, and only 3 results in the 1% to 0.9% range, the rest being smaller; evidence that the Challenge 2 solutions were generally very good and probably nearly optimal.
The spreadsheet has 10 tabs, with the Nov1 tab holding the final results. Other tabs have submission information, team information, and other intermediate data.",
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"description": "Complete results for all 15 teams participating in Challenge 2 Event 3 that closed June 30, 2021. The evaluations were completed on July 29, 2021, at 01:01. Each of 4 divisions used 66 scenarios resulting in 3960 data rows (4*66*15) in the data tab. There is additional information about the teams, the data, scoring by divisions, leaderboard summaries, and more. $600k in prizes were awarded to the following teams:
Artelys $170k
Electric Stampede $140k
GravityX $130k
Pearl Street Technologies $70k
GMI-GO $60k",
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"title": "Challenge 2 Final Event Results.xlsx",
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"description": "Complete results for all 16 teams participating in Challenge 2 Final Event that closed August 13, 2021. The evaluations were completed on September 30, 2021, at 21:29. Each of 4 divisions used 120 scenarios resulting in 7,680 data rows (4*120*16) in the data tab. There is additional information about the teams, the data, scoring by divisions, leaderboard summaries, and more. $1800k in prizes were awarded to the following teams:
GravityX $600k
GOT-BSI-OPF $420k
Artelys $360k
Pearl Street Technologies $270k
GMI-GO $60k
Monday Mornings $60k
GO-SNIP $30k",
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"title": "Challenge 2 Problem Formulation.pdf",
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"description": "Document containing mathematical problem definition and several appendices that describe properties of the input and output data and their required formats.
The optimization problem is a mixed integer, non-linear, non-convex (MINLP) problem and includes discrete variables such as unit commitment, control settings (transformer taps with impedance correction tables) and bus shunts.
Divisions 1 and 2 will allow competitors to use any feature of the loads, generators, and transmission assets described in the formulation and within the limits of the input datasets to optimize each scenario for both the base case and each contingency response except for topology optimization (line switching).
Divisions 3 and 4 will allow competitors to employ all these previously described features as well as topology optimization. See the Challenge 2 scoring document for details.
",
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"description": "Four scenarios from network model C2S9N02020. These synthetic datasets reflect a unique data feature for phase shifting transformers that is within the problem formulation but was not well-represented in the synthetic examples in the trial events. It is, however, present in some of the industry scenarios used with the Final Event. The network model has 1,392 loads, 194 generators, 2,318 lines, 538 transformers, 0 fixed shunts, and 98 switched shunts. Scenario 250 has 54 generator contingencies, 202 branch contingencies, and MSpp 4,131,867. Scenario 255 has 80 generator contingencies, 182 branch contingencies, and MSpp 5,228,247. Scenario 260 has 69 generator contingencies, 190 branch contingencies, and MSpp 5,855,728. Scenario 270 has 67 generator contingencies, 191 branch contingencies, and MSpp 4,943,650.",
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"description": "Scenarios developed for Challenge 2 Final Event but never used. Includes C2FEN00617 (74 scenarios), C2FEN02020 (159 scenarios), C2FEN02312 (10 scenarios), C2FEN03288 (27 scenarios), and C2FEN04200 (170 scenarios).",
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"description": "Scenarios developed for Challenge 2 Final Event but never used. Includes C2FEN10480 (24 scenarios), C2FEN12209 (93 scenarios), and C2FEN19402 (63 scenarios).",
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"title": "Challenge 2 Sandbox Data C2S6N00617 Scenarios.zip",
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"description": "Ten scenarios from network model C2S6N00617.",
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"title": "Challenge 2 Event 3 Synthetic Data Scenarios.zip",
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"description": "The 11 synthetic networks (2020-, 3022-, 4200-, 4917-, 6100-, 7000-, 8300-, 10000-, 12209-, 30000-, and 31777-buses), composed of 54 scenarios used in Challenge 2 Event 3. The 3 industry networks (3593-,19955-, and 22700-buses) used, composed of 12 scenarios, are not publicly available. Three scenarios (C2T3N06100/39, C2T3N07000/65, and C2T3N08300/34) had negative MSpp values. This was allowed because the base contribution from the prior operating point was positive and only the contingency part was negative; optimal Market Surplus values were positive.
See Dan Bienstock's talk at the 2022 FERC Software Conference, https://www.ferc.gov/media/solving-go-competition-acopf-problems, slide 17, for a diagram of network C2T3N06100 scenario 115.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Event_3_Synthetic_Data_Scenarios.zip"
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"title": "Challenge 2 Trial Event 1 Synthetic Data Scenarios.zip",
"format": "zip",
"mediaType": "application/zip",
"description": "The 11 synthetic networks (500-, 617-, 768-, 2020-, 2055-, 2312-, 5746-, 6469-, 8028-, 14204-, and 15810-buses), composed of 63 scenarios used in Challenge 2 Trial Event 1. The 4 industry datasets (403-, 3411-, 4441-, and 16955-buses) used, composed of 20 scenarios, are not publicly available.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Trial_Event_1_Synthetic_Data_Scenarios.zip"
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{
"@type": "dcat:Distribution",
"title": "Challenge 2 Trial Event 2 Synthetic Data Scenarios.zip",
"format": "zip",
"mediaType": "application/zip",
"description": "The 13 synthetic networks (617-, 2020-, 3022-, 4200-, 4917-, 6100-, 7000-, 8300-, 10000-, 12209-, 17700-, 30000-, and 31777-buses), composed of 54 scenarios used in Challenge 2 Trial Event 2. The 4 industry networks (1737-, 3593-, 6705-, 34363-buses) used, composed of 14 scenarios, are not publicly available.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Trial_Event_2_Synthetic_Data_Scenarios.zip"
},
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"title": "Challenge 2 Final Event 4 Synthetic Data Scenarios.zip",
"format": "zip",
"mediaType": "application/zip",
"description": "The 16 synthetic networks (617-, 2020-, 2312-, 3288-, 3970-, 4200-, 4601-, 6100-, 7000-, 8300-, 8718-, 10480-, 12209-, 17700-, 19402-, and 31777-buses), composed of 84 scenarios used in Challenge 2 Final Event 4. The 6 industry networks (403-, 3411-, 3593-, and 6705-buses), composed of 36 scenarios, are not publicly available. The full Challenge 2 Final Event dataset consisted of 22 networks and 120 scenarios.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2%20_Final_Event_4_Synthetic_Data_Scenarios.zip"
},
{
"@type": "dcat:Distribution",
"title": "Challenge 2 Rules.pdf",
"format": "pdf",
"mediaType": "application/pdf",
"description": "The Challenge 2 Rules Document PDF explains the eligibility requirements and restrictions for awards to Entrants. This covers the technological approach, team members (including minors), registration, awards, intellectual property, use of proprietary software, trademarks, and additional information. Also discussed are scope and precedence and general conditions including both Entrant and Government Representations and Warranties, personally identifiable information, relationship of the parties, and trademark license.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Rules.pdf"
},
{
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"title": "Challenge 2 Scoring.pdf",
"format": "pdf",
"mediaType": "application/pdf",
"description": "The Challenge 2 Scoring Document PDF clarifies the terminology, scoring divisions, prize categories, and the use of transmission line and transformer switching. Transmission line and transformer switching may only be done in Divisions 3 and 4. No transmission line and transformer switching was allowed in Divisions 1 and 2.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Scoring.pdf"
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"@type": "dcat:Distribution",
"title": "Challenge 2 Timeline.pdf",
"format": "pdf",
"mediaType": "application/pdf",
"description": "The Challenge 2 Timeline Document PDF lays out timing of Challenge 2 Events, including registration and submission deadlines and the release of results and datasets.
",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Timeline.pdf"
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"@type": "dcat:Distribution",
"title": "Challenge 2 Trial Event 2 Results.xlsx",
"format": "xlsx",
"mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"description": "This spreadsheet contains 12 tabs. The Evaluation Results are in the data tab, the leaderboard results are in the “Msgain tables” tab, the list of participating teams is in the teams tab and information about the datasets is in the “dataset list 68” tab.
The meaning of the first 4 columns of the data tab should be obvious: team (name), (network) model, scenario (number), and division (1-4).
The next 3 are the scoring elements. The scenario score is the maximum of zpp and the objective, which is the Market Surplus obtained from the two solution files. If it is blank, Evaluation was unable to obtain a value for one of several possible reasons: one or both solution files were missing, incomplete, or defective. The team score over a given set S of scenarios is the sum of the scenario scores.
The last_scored_time is the timestamp from when the Evaluation was completed.
The infeasible column will contain “1” if Evaluation found the solution to be infeasible, which also happens if any switching is done in divisions 1 or 2. If no solution1 file is found the cell will be blank.
The sol1_created column will contain “1” if a BASECASE.txt file (also known as solution1 or sol1) is found; the sol2_created column will contain “1” if the appropriate number of “solution_label.txt” files (also known as solution2 or sol2) are found. Both columns need to be 1 and infeasible must be 0 to calculate the objective value. It may be 1 but the files may be invalid, which is probably the case if sol1_created is 1 but srun2_state is blank. This is not the case when the number of 0 entries is the same as the number of blank srun2_states, which are highlighted when it occurs.
The code1_runtime, code2_runtime, and eval_runtime columns give the number of seconds used for each purpose. The code1 time limit is either 300 seconds (divisions 1 and 3) or 3600 seconds (division 2 and 4). The code2 time limit is given in the code2_timelimit column (AD). The Eval runtime is for platform diagnostics.
The srun1_state and srun2_state columns give the completion status for codes 1 and 2. Exceeding the time limit may result in a CANCELLED status, which is not bad if the appropriate valid solution files were created. The same is true for FAILED status. The appropriate codex_err message may be helpful. CANCELLED+ indicates additional information was truncated; check the codex_err column. The srun2_state will be blank if no solution1.txt was generated.
The code1_err and code2_err columns provide additional error message information. One of the most common messages is that the run was cancelled due to time limit, which should also be indicated in the code1 or code2 timedout columns.
The code1_done (column BB) and code2_done (column BC) columns with a 1 indicate the code was run. Code1 executes in every case, but code2 does not execute if there is a problem with the solution files.
The contingency_count column (BE) gives the number of contingencies for a scenario, the sec_per_contingency column (BF) tells how long it took to evaluate each contingency, and the code2_timelimit column (BG) uses the contingency_count to compute the time limit for code2 for a scenario.
The code1_exitcode (column BJ) and code2_exitcode (BK) columns show the exit code returned by the given code. These can depend on the language being used. A code of 0 indicates a normal exit, 1 is an unspecified failure, 126 indicates the command was found but could not be executed (likely because the run had timed out), 127 indicates the run timed out, 134 indicated the run was aborted, 135 is a bus error, 137 is a forced termination, and 139 is a segmentation fault (address out of bounds, typically due to an invalid index value.
The url column (BR) holds the address where the results tar file may be downloaded from.
Data from the Evaluation program starts in column BU and may be understood from the comments in the code that is available at https://github.com/GOCompetition/C2DataUtilities. Reruns (column LD) tells how many times the solution/Evaluation package was run for this scenario. Trial Event 2 required a total of 5593 runs, 13.5% more than the minimum.",
"downloadURL": "https://data.openei.org/files/6197/Challenge_2_Trial_Event_2_Results.xlsx"
}
]
|
| DOI | 10.25984/2448433 |
| identifier | https://data.openei.org/submissions/6197 |
| issued | 2024-09-20T06:00:00Z |
| keyword |
[
"ACOPF",
"ARPA-E",
"GO Competition",
"Unit Commitment",
"challenge 2",
"competition",
"computational science",
"energy",
"energy model",
"grid",
"grid optimization",
"model",
"multiperiod",
"multiperiod dynamic markets",
"optimization",
"power",
"security-constrained optimal power flow"
]
|
| landingPage | https://data.openei.org/submissions/6197 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2025-01-02T16:46:01Z |
| programCode |
[
"019:000",
"019:023"
]
|
| projectNumber | CJ0000903 |
| projectTitle | ARPA-E Grid Optimization Competition |
| publisher |
{
"name": "Pacific Northwest National Laboratory",
"@type": "org:Organization"
}
|
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"{"type":"Polygon","coordinates":[[[-167.7267,13.518],[-53.8316,13.518],[-53.8316,75.0714],[-167.7267,75.0714],[-167.7267,13.518]]]}"
|
| title | ARPA-E Grid Optimization (GO) Competition Challenge 2 |
