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Datasets:
PGLearn
/
PGLearn-Small

Tasks:
Tabular Regression
Size:
1M<n<10M
Tags:
energy
optimization
optimal_power_flow
power_grid
License:
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metadata
license: cc-by-sa-4.0
tags:
  - energy
  - optimization
  - optimal_power_flow
  - power_grid
pretty_name: PGLearn Optimal Power Flow (small)
size_categories:
  - 100K<n<1M
task_categories:
  - tabular-regression
viewer: false

PGLearn optimal power flow (small) dataset

This dataset contains input data and solutions for small-size Optimal Power Flow (OPF) problems. Original case files are based on instances from Power Grid Lib -- Optimal Power Flow (PGLib OPF); this dataset comprises instances corresponding to systems with up to 300 buses.

Contents

For each system (e.g., 14_ieee, 118_ieee), the dataset provides multiple OPF instances, and corresponding primal and dual solutions for the following OPF formulations

  • AC-OPF (nonlinear, non-convex)
  • DC-OPF approximation (linear, convex)
  • Second-Order Cone (SOC) relaxation of AC-OPF (nonlinear, convex)

This dataset was created using OPFGenerator; please see the OPFGenerator documentation for details on mathematical formulations.

Use cases

The primary intended use case of this dataset is to learn a mapping from input data to primal and/or dual solutions.