Quantum mechanics

Engineering

Sophistication

Aerospace engineering

Variety (cybernetics)

Open source

Range (aeronautics)

Power (physics)

Computer science

Mathematical optimization

Distributed computing

Software

Thermodynamics

Physics

Power flow

Mathematics

Flow (mathematics)

Electric power system

Industrial engineering

Power-flow study

Sociology

Artificial intelligence

Geometry

Programming language

Mechanics

Social science

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.

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