mlsanityData to 7 Oct 2026

AC Power Flow Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE

arXiv 1603.01533 ↗First posted 4 Mar 2016math.OCcited by 15

Not on the map. Why?

Abstract (arXiv)

In this paper, we publish nine new test cases in MATPOWER format. Four test cases are French very high-voltage grid generated by the offline plateform of iTesla: part of the data was sampled. Four test cases are RTE snapshots of the full French very high-voltage and high-voltage grid that come from French SCADAs via the Convergence software. The ninth and largest test case is a pan-European ficticious data set that stems from the PEGASE project. It complements the four PEGASE test cases that we previously published in MATPOWER version 5.1 in March 2015. We also provide a MATLAB code to transform the data into standard mathematical optimization format. Computational results confirming the validity of the data are presented in this paper.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Mar 2016.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 1; 2023: 3; 2024: 4; 2025: 2; 2026: 2.

15 papers.

Sort:

  1. 2023End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatchcited by 35
  2. 2024OPFData: Large-scale datasets for AC optimal power flow with topological perturbationscited by 22
  3. 2021Power Flow Balancing with Decentralized Graph Neural Networkscited by 19
  4. 2023PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networkscited by 19
  5. 2025PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flowcited by 11
  6. 2021Cyberattack Detection in Large-Scale Smart Grids using Chebyshev Graph Convolutional Networkscited by 8
  7. 2024Transmission Interface Power Flow Adjustment: A Deep Reinforcement Learning Approach based on Multi-task Attribution Mapcited by 6
  8. 2024Powerformer: A Section-adaptive Transformer for Power Flow Adjustmentcited by 5
  9. 2025PFDelta: A Benchmark Dataset for Power Flow under Load, Generation, and Topology Variationscited by 4
  10. 2022On the Exactness of Dantzig-Wolfe Relaxation for Rank Constrained Optimization Problemscited by 3
  11. 2021Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecastingcited by 2
  12. 2024Graph neural networks for power grid operational risk assessment under evolving grid topologycited by 1
3 more
  1. 2023Operational risk quantification of power grids using graph neural network surrogates of the DC OPFcited by 0
  2. 2026PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow with Continual Learningcited by 0
  3. 2026Differentiable Power-Flow Optimizationcited by 0