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Benchmarking Large-Scale ACOPF Solutions and Optimality Bounds by Gopinath, Smitha; Hijazi, Hassan L. is a scholarly article available to read on EtoBox.

What is Benchmarking Large-Scale ACOPF Solutions and Optimality Bounds about?

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.

Author

Gopinath, Smitha; Hijazi, Hassan L.

Published

2022

Language

EN