  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.
