Complete results for a numerical evaluation of interior point solvers for large-scale optimal power flow problems

TL;DR

This paper evaluates the performance of various interior point solvers across multiple large-scale optimal power flow formulations, providing comprehensive benchmarks on robustness, efficiency, and reliability.

Contribution

It offers the first extensive numerical comparison of interior point methods for different OPF formulations on large power networks within the Matpower platform.

Findings

Polar-Current formulation shows high robustness.

Cartesian-Power method is fastest on average.

Performance varies significantly with network size and initial guess.

Abstract

Recent advances in open source interior-point optimization methods and power system related software have provided researchers and educators with the necessary platform for simulating and optimizing power networks with unprecedented convenience. Within the Matpower software platform a combination of several different interior point optimization methods are provided and four different optimal power flow (OPF) formulations are recently available: the Polar-Power, Polar-Current, Cartesian-Power, and Cartesian-Current. The robustness and reliability of interior-point methods for different OPF formulations for minimizing the generation cost starting from different initial guesses, for a wide range of networks provided in the Matpower library ranging from 1951 buses to 193000 buses, will be investigated. Performance profiles are presented for iteration counts, overall time, and memory consumption, revealing the most reliable optimization method for the particular metric.