license:mit region:us
---
license: mit
---

This page hosts the [PGLearn](https://huggingface.co/PGLearn) dataset [`14_ieee_011025`](https://huggingface.co/datasets/PGLearn/14_ieee_011025), containing 1,000,000 samples of ACOPF, DCOPF, and SOCOPF primal and dual solutions for varying loads on the [`14_ieee`](https://github.com/power-grid-lib/pglib-opf/blob/master/pglib_opf_case14_ieee.m) benchmark from [pglib-opf](https://github.com/power-grid-lib/pglib-opf).

The dataset was generated using the [OPFGenerator](https://github.com/AI4OPT/OPFGenerator) repository; please refer to the documentation therein for more details.

Load vectors are sampled by applying one global `Uniform(0.8, 1.2)` factor per sample, then a local `Uniform(0.8, 1.2)` factor per load. This corresponds to `ScaledUniform(l=0.8, u=1.2, sigma=0.2)` in [OPFGenerator](https://github.com/AI4OPT/OPFGenerator). Network data is pre-processed using [PowerModels.make_basic_network](https://lanl-ansi.github.io/PowerModels.jl/stable/basic-data-utilities/#PowerModels.make_basic_network).
