Grid Optimization Competition on Synthetic and Industrial Power Systems

Farnaz Safdarian; Jonathan Snodgrass; Ju Hee Yeo; Adam Birchfield; Carleton Coffrin; Chris Demarco; Stephen Elbert; Brent Eldridge; Tarek Elgindy; Scott L. Greene; Nongchao Guo; Jesse Holzer; Bernard Lesieutre; Hans Mittelmann; Richard P. O'Neill; Thomas J. Overbye; Bryan Palmintier; Pascal Van Hentenryck; Arun Veeramany; Terrence W.K. Mak; Jessica Wert

doi:10.1109/NAPS56150.2022.10012138

Grid Optimization Competition on Synthetic and Industrial Power Systems

Farnaz Safdarian, Jonathan Snodgrass, Ju Hee Yeo, Adam Birchfield, Carleton Coffrin, Chris Demarco, Stephen Elbert, Brent Eldridge, Tarek Elgindy, Scott L. Greene, Nongchao Guo, Jesse Holzer, Bernard Lesieutre, Hans Mittelmann, Richard P. O'Neill, Thomas J. Overbye, Bryan Palmintier, Pascal Van Hentenryck, Arun Veeramany, Terrence W.K. MakJessica Wert

Mathematical and Statistical Sciences, School of (SoMSS)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.

Original language	English (US)
Title of host publication	2022 North American Power Symposium, NAPS 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665499217
DOIs	https://doi.org/10.1109/NAPS56150.2022.10012138
State	Published - 2022
Event	2022 North American Power Symposium, NAPS 2022 - Salt Lake City, United States Duration: Oct 9 2022 → Oct 11 2022

Publication series

Name	2022 North American Power Symposium, NAPS 2022

Conference

Conference	2022 North American Power Symposium, NAPS 2022
Country/Territory	United States
City	Salt Lake City
Period	10/9/22 → 10/11/22

Keywords

Mixed-integer non-linear programming
optimal power flow
optimization
power systems
synthetic network models

ASJC Scopus subject areas

Computer Networks and Communications
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Control and Optimization

Access to Document

10.1109/NAPS56150.2022.10012138

Cite this

Safdarian, F., Snodgrass, J., Yeo, J. H., Birchfield, A., Coffrin, C., Demarco, C., Elbert, S., Eldridge, B., Elgindy, T., Greene, S. L., Guo, N., Holzer, J., Lesieutre, B., Mittelmann, H., O'Neill, R. P., Overbye, T. J., Palmintier, B., Van Hentenryck, P., Veeramany, A., ... Wert, J. (2022). Grid Optimization Competition on Synthetic and Industrial Power Systems. In 2022 North American Power Symposium, NAPS 2022 (2022 North American Power Symposium, NAPS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAPS56150.2022.10012138

Grid Optimization Competition on Synthetic and Industrial Power Systems. / Safdarian, Farnaz; Snodgrass, Jonathan; Yeo, Ju Hee et al.
2022 North American Power Symposium, NAPS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 North American Power Symposium, NAPS 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Safdarian, F, Snodgrass, J, Yeo, JH, Birchfield, A, Coffrin, C, Demarco, C, Elbert, S, Eldridge, B, Elgindy, T, Greene, SL, Guo, N, Holzer, J, Lesieutre, B, Mittelmann, H, O'Neill, RP, Overbye, TJ, Palmintier, B, Van Hentenryck, P, Veeramany, A, Mak, TWK & Wert, J 2022, Grid Optimization Competition on Synthetic and Industrial Power Systems. in 2022 North American Power Symposium, NAPS 2022. 2022 North American Power Symposium, NAPS 2022, Institute of Electrical and Electronics Engineers Inc., 2022 North American Power Symposium, NAPS 2022, Salt Lake City, United States, 10/9/22. https://doi.org/10.1109/NAPS56150.2022.10012138

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title = "Grid Optimization Competition on Synthetic and Industrial Power Systems",

abstract = "This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.",

keywords = "Mixed-integer non-linear programming, optimal power flow, optimization, power systems, synthetic network models",

author = "Farnaz Safdarian and Jonathan Snodgrass and Yeo, {Ju Hee} and Adam Birchfield and Carleton Coffrin and Chris Demarco and Stephen Elbert and Brent Eldridge and Tarek Elgindy and Greene, {Scott L.} and Nongchao Guo and Jesse Holzer and Bernard Lesieutre and Hans Mittelmann and O'Neill, {Richard P.} and Overbye, {Thomas J.} and Bryan Palmintier and {Van Hentenryck}, Pascal and Arun Veeramany and Mak, {Terrence W.K.} and Jessica Wert",

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year = "2022",

doi = "10.1109/NAPS56150.2022.10012138",

language = "English (US)",

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AU - Demarco, Chris

AU - Elbert, Stephen

AU - Eldridge, Brent

AU - Elgindy, Tarek

AU - Greene, Scott L.

AU - Guo, Nongchao

AU - Holzer, Jesse

AU - Lesieutre, Bernard

AU - Mittelmann, Hans

AU - O'Neill, Richard P.

AU - Overbye, Thomas J.

AU - Palmintier, Bryan

AU - Van Hentenryck, Pascal

AU - Veeramany, Arun

AU - Mak, Terrence W.K.

AU - Wert, Jessica

PY - 2022

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N2 - This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.

AB - This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.

KW - Mixed-integer non-linear programming

KW - optimal power flow

KW - optimization

KW - power systems

KW - synthetic network models

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Grid Optimization Competition on Synthetic and Industrial Power Systems

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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