Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition
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Abstract (arXiv)
The optimal power flow problem is central to many tasks in the design and operation of electric power grids. This problem seeks the minimum cost operating point for an electric power grid while satisfying both engineering requirements and physical laws describing how power flows through the electric network. By additionally considering the possibility of component failures and using an accurate AC power flow model of the electric network, the security-constrained AC optimal power flow (SC-AC-OPF) problem is of paramount practical relevance. To assess recent progress in solution algorithms for SC-AC-OPF problems and spur new innovations, the U.S. Department of Energy's Advanced Research Projects Agency--Energy (ARPA-E) organized Challenge 1 of the Grid Optimization (GO) competition. This paper describes the SC-AC-OPF problem formulation used in the competition, overviews historical developments and the state of the art in SC-AC-OPF algorithms, discusses the competition, and summarizes the algorithms used by the top three teams in Challenge 1 of the GO Competition (Teams gollnlp, GO-SNIP, and GMI-GO).
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Jun 2022.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 2.
6 papers.
- 2022Unsupervised Optimal Power Flow Using Graph Neural Networkscited by 14
- 2023Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flowcited by 3
- 2024Formulations and scalability of neural network surrogates in nonlinear optimization problemscited by 1
- 2025Nonlinear Optimization with GPU-Accelerated Neural Network Constraintscited by 1
- 2024Online Planning of Power Flows for Power Systems Against Bushfires Using Spatial Contextcited by 0
- 2025Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutionscited by 0
- 2025Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutions17 Oct 2025
- 2025Nonlinear Optimization with GPU-Accelerated Neural Network Constraints26 Sep 2025
- 2024Formulations and scalability of neural network surrogates in nonlinear optimization problems16 Dec 2024
- 2024Online Planning of Power Flows for Power Systems Against Bushfires Using Spatial Context20 Apr 2024
- 2023Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow29 Nov 2023
- 2022Unsupervised Optimal Power Flow Using Graph Neural Networks17 Oct 2022