PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations

Carleton Coffrin, Russell Bent, Kaarthik Sundar, Yeesian Ng, Miles Lubin
11/6/2017
math.OCcs.CE

Official code: lanl-ansi/PowerModels.jl (486 stars, last commit 2026-10-08). 1 more implementation below.

Abstract

In recent years, the power system research community has seen an explosion of novel methods for formulating and solving power network optimization problems. These emerging methods range from new power flow approximations, which go beyond the traditional DC power flow by capturing reactive power, to convex relaxations, which provide solution quality and runtime performance guarantees. Unfortunately, the sophistication of these emerging methods often presents a significant barrier to evaluating them on a wide variety of power system optimization applications. To address this issue, this work proposes PowerModels, an open-source platform for comparing power flow formulations. From its inception, PowerModels was designed to streamline the process of evaluating different power flow formulations on shared optimization problem specifications. This work provides a brief introduction to the design of PowerModels, validates its implementation, and demonstrates its effectiveness with a proof-of-concept study analyzing five different formulations of the Optimal Power Flow problem.

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Code Implementations(2)

A Julia/JuMP Package for Power Network Optimization

486172Julia, MATLABAug 1, 20161 weeks agoNOASSERTION
networkoptimal-power-flowoptimizationpower-network
MIT

Repo containing supplementary data and code for the "Probabilistic N-k Failure Identification for Power Systems"

54Julia, ShellNov 8, 20166 years agoMIT

Cite this paper

@article{coffrin2017powermodelsjl,
  title  = {PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations},
  author = {Carleton Coffrin and Russell Bent and Kaarthik Sundar and Yeesian Ng and Miles Lubin},
  year   = {2017},
  eprint = {1711.01728},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1711.01728}
}

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