# NESTA, The NICTA Energy System Test Case Archive

arXiv: https://arxiv.org/abs/1411.0359 · HTML: https://mlsanity.com/paper/1411.0359/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2014.

## Built on by (most cited first, 9 of 9)

- [Learning Hard Optimization Problems: A Data Generation Perspective](https://mlsanity.com/paper/2106.02601/) (2021)
- [Data-Driven Time Series Reconstruction for Modern Power Systems Research](https://mlsanity.com/paper/2110.13772/) (2021)
- [Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization](https://mlsanity.com/paper/2311.13087/) (2023)
- [Learning Joint Models of Prediction and Optimization](https://mlsanity.com/paper/2409.04898/) (2024)
- [Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization](https://mlsanity.com/paper/2312.17394/) (2023)
- [Towards Systematic Generalization for Power Grid Optimization Problems](https://mlsanity.com/paper/2605.02026/) (2026)
- [Load Encoding for Learning AC-OPF](https://mlsanity.com/paper/2101.03973/) (2021)
- [Realistic Differentially-Private Transmission Power Flow Data Release](https://mlsanity.com/paper/2103.14036/) (2021)
- [Towards Understanding the Unreasonable Effectiveness of Learning AC-OPF Solutions](https://mlsanity.com/paper/2111.11168/) (2021)

## Abstract (arXiv)

In recent years the power systems research community has seen an explosion of work applying operations research techniques to challenging power network optimization problems. Regardless of the application under consideration, all of these works rely on power system test cases for evaluation and validation. However, many of the well established power system test cases were developed as far back as the 1960s with the aim of testing AC power flow algorithms. It is unclear if these power flow test cases are suitable for power system optimization studies. This report surveys all of the publicly available AC transmission system test cases, to the best of our knowledge, and assess their suitability for optimization tasks. It finds that many of the traditional test cases are missing key network operation constraints, such as line thermal limits and generator capability curves. To incorporate these missing constraints, data driven models are developed from a variety of publicly available data sources. The resulting extended test cases form a compressive archive, NESTA, for the evaluation and validation of power system optimization algorithms.