mlsanityData to 14 Oct 2026

Learning Warm-Start Points for AC Optimal Power Flow

arXiv 1905.08860 ↗First posted 21 May 2019math.OC eess.SPcited by 32

Not on the map. Why?

Abstract (arXiv)

A large amount of data has been generated by grid operators solving AC optimal power flow (ACOPF) throughout the years, and we explore how leveraging this data can be used to help solve future ACOPF problems. We use this data to train a Random Forest to predict solutions of future ACOPF problems. To preserve correlations and relationships between predicted variables, we utilize a multi-target approach to learn approximate voltage and generation solutions to ACOPF problems directly by only using network loads, without the knowledge of other network parameters or the system topology. We explore the benefits of using the learned solution as an intelligent warm start point for solving the ACOPF, and the proposed framework is evaluated numerically using multiple IEEE test networks. The benefit of using learned ACOPF solutions is shown to be solver and network dependent, but shows promise for quickly finding approximate solutions to the ACOPF problem.

Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 May 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 7; 2022: 5; 2023: 4; 2024: 3; 2025: 6; 2026: 7.

32 papers.

Sort:

By area:

  1. 2021DC3: A learning method for optimization with hard constraintscited by 184
  2. 2022Tutorial on amortized optimizationcited by 83
  3. 2023Learning to Warm-Start Fixed-Point Optimization Algorithmscited by 32
  4. 2022Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutionscited by 28
  5. 2021Leveraging power grid topology in machine learning assisted optimal power flowcited by 22
  6. 2021OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasetscited by 18
  7. 2021Spatial Network Decomposition for Fast and Scalable AC-OPF Learningcited by 15
  8. 2022Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitmentscited by 12
  9. 2025Generating Symbolic World Models via Test-time Scaling of Large Language Modelscited by 12
  10. 2023Compact Optimization Learning for AC Optimal Power Flowcited by 11
  11. 2022Learning Regionally Decentralized AC Optimal Power Flows with ADMMcited by 7
  12. 2021Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problemscited by 6
20 more
  1. 2025Towards Generalization of Graph Neural Networks for AC Optimal Power Flowcited by 6
  2. 2021Graph Neural Networks for Learning Real-Time Prices in Electricity Marketcited by 5
  3. 2024QCQP-Net: Reliably Learning Feasible Alternating Current Optimal Power Flow Solutions Under Constraintscited by 5
  4. 2024Data-Driven Performance Guarantees for Classical and Learned Optimizerscited by 5
  5. 2024Learning Multiple Initial Solutions to Optimization Problemscited by 4
  6. 2021Scalable Learning for Optimal Load Shedding Under Power Grid Emergency Operationscited by 3
  7. 2025Constrained Diffusion Models for Synthesizing Representative Power Flow Datasetscited by 2
  8. 2022Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systemscited by 1
  9. 2025Diffusion-based learning framework for Constrained Nonconvex Optimization with Weighted Bootstrapped Refinementcited by 1
  10. 2026LEAF: A Learning-Enabled ADMM Framework for Accelerated Convex Optimizationcited by 1
  11. 2023AI Driven Near Real-time Locational Marginal Pricing Method: A Feasibility and Robustness Studycited by 0
  12. 2023Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifiercited by 0
  13. 2025Study Design and Demystification of Physics Informed Neural Networks for Power Flow Simulationcited by 0
  14. 2025Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutionscited by 0
  15. 2026Learning efficient representations of complex constraints for scalable optimizationcited by 0
  16. 2026WARP: A Benchmark for Primal-Dual Warm-Starting of Interior-Point Solverscited by 0
  17. 2026Learning-enabled Acceleration of Scenario-based Model Predictive Controlcited by 0
  18. 2026When Do Learned Diffusion Proposals Help Constraint Solving? A Controlled Study on Continuous Algebraic Systemscited by 0
  19. 2026Graph Machine Learning: An Opportunity for Power Systemscited by 0
  20. 2026Scalable Self-Supervised Learning for Multiphase AC-OPF in Distribution Systems with Topology Reconfigurationcited by 0