Solutions of DC OPF are Never AC Feasible
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Abstract (arXiv)
In this paper, we analyze the relationship between generation dispatch solutions produced by the DC optimal power flow (DC OPF) problem by the AC optimal power flow (AC OPF) problem. While there has been much previous work in analyzing the approximation error of the DC assumption, the AC feasibility has not been fully explored, although difficulty achieving AC feasibility is known in practice. Here, we consider the set of feasible points in a standard DC OPF problem and the set of feasible points in a standard AC OPF problem. Under some very light assumptions, we show that the intersection of these sets is the empty set; i.e., that no solution to the DC OPF problem will satisfy the AC power flow constraints. Then, it is demonstrated that even with generation adjustments in DC OPF to account for losses, DC OPF solutions are still not AC feasible.
Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Dec 2019.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 2; 2024: 6; 2025: 2.
16 papers.
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- 2024CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbationscited by 27
- 2024OPFData: Large-scale datasets for AC optimal power flow with topological perturbationscited by 22
- 2021Leveraging power grid topology in machine learning assisted optimal power flowcited by 21
- 2021Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitmentcited by 17
- 2022Learning Regionally Decentralized AC Optimal Power Flows with ADMMcited by 7
- 2021Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problemscited by 6
- 2025Towards Generalization of Graph Neural Networks for AC Optimal Power Flowcited by 5
- 2021Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plantscited by 4
- 2022Unsupervised Deep Learning for AC Optimal Power Flow via Lagrangian Dualitycited by 3
- 2024Optimal Power Grid Operations with Foundation Modelscited by 2
- 2023Quantum Neural Networks for Power Flow Analysiscited by 1
- 2024Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flowcited by 1
4 more
- 2024Physics-Informed Graph Neural Networks for Robust AC-Optimal Power Flowcited by 1
- 2023Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifiercited by 0
- 2024Data-Driven Stochastic AC-OPF using Gaussian Processescited by 0
- 2025Dynamic Domain Adaptation-Driven Physics-Informed Graph Representation Learning for AC-OPFcited by 0
- 2025Towards Generalization of Graph Neural Networks for AC Optimal Power Flow8 Oct 2025
- 2025Dynamic Domain Adaptation-Driven Physics-Informed Graph Representation Learning for AC-OPF31 May 2025
- 2024Physics-Informed Graph Neural Networks for Robust AC-Optimal Power Flow7 Oct 2024
- 2024Optimal Power Grid Operations with Foundation Models3 Sep 2024
- 2024Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow30 Jul 2024
- 2024OPFData: Large-scale datasets for AC optimal power flow with topological perturbations11 Jun 2024
- 2024CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations26 Mar 2024
- 2024Data-Driven Stochastic AC-OPF using Gaussian Processes17 Feb 2024
- 2023Quantum Neural Networks for Power Flow Analysis4 Nov 2023
- 2023Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifier7 Oct 2023
- 2022Unsupervised Deep Learning for AC Optimal Power Flow via Lagrangian Duality7 Dec 2022
- 2022Learning Regionally Decentralized AC Optimal Power Flows with ADMM8 May 2022
4 more
- 2021Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problems15 Dec 2021
- 2021Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment21 Oct 2021
- 2021Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plants6 Oct 2021
- 2021Leveraging power grid topology in machine learning assisted optimal power flow1 Oct 2021
- 2024CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbationscited by 27
- 2024OPFData: Large-scale datasets for AC optimal power flow with topological perturbationscited by 22
- 2021Leveraging power grid topology in machine learning assisted optimal power flowcited by 21
- 2021Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitmentcited by 17
- 2022Learning Regionally Decentralized AC Optimal Power Flows with ADMMcited by 7
- 2021Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problemscited by 6
- 2025Towards Generalization of Graph Neural Networks for AC Optimal Power Flowcited by 5
- 2021Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plantscited by 4
- 2022Unsupervised Deep Learning for AC Optimal Power Flow via Lagrangian Dualitycited by 3
- 2024Optimal Power Grid Operations with Foundation Modelscited by 2
- 2023Quantum Neural Networks for Power Flow Analysiscited by 1
- 2024Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flowcited by 1
12 most cited of 16 All 16 (JSON)
- 2025Towards Generalization of Graph Neural Networks for AC Optimal Power Flow8 Oct 2025
- 2025Dynamic Domain Adaptation-Driven Physics-Informed Graph Representation Learning for AC-OPF31 May 2025
- 2024Physics-Informed Graph Neural Networks for Robust AC-Optimal Power Flow7 Oct 2024
- 2024Optimal Power Grid Operations with Foundation Models3 Sep 2024
- 2024Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow30 Jul 2024
- 2024OPFData: Large-scale datasets for AC optimal power flow with topological perturbations11 Jun 2024
- 2024CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations26 Mar 2024
- 2024Data-Driven Stochastic AC-OPF using Gaussian Processes17 Feb 2024
- 2023Quantum Neural Networks for Power Flow Analysis4 Nov 2023
- 2023Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifier7 Oct 2023
- 2022Unsupervised Deep Learning for AC Optimal Power Flow via Lagrangian Duality7 Dec 2022
- 2022Learning Regionally Decentralized AC Optimal Power Flows with ADMM8 May 2022
12 newest of 16 All 16 (JSON)