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arXiv · 2203.11328

Benchmarking Large-Scale ACOPF Solutions and Optimality Bounds

Smitha Gopinath·Hassan L. Hijazi
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Abstract

We present the results of a comprehensive benchmarking effort aimed at evaluating and comparing state-of-the-art open-source tools for solving the Alternating-Current Optimal Power Flow (ACOPF) problem. Our numerical experiments include all instances found in the public library PGLIB with network sizes up to 30,000 nodes. The benchmarked tools span a number of programming languages (Python, Julia, Matlab/Octave, and C$++$), nonlinear optimization solvers (Ipopt, MIPS, and INLP) as well as different mathematical modeling tools (JuMP and Gravity). We also present state-of-the-art optimality bounds obtained using sparsity-exploiting semidefinite programming approaches and corresponding computational times.

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Smitha Gopinath, Hassan L. Hijazi. 2022-03-21. Benchmarking Large-Scale ACOPF Solutions and Optimality Bounds. https://arxiv.org/abs/2203.11328

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