PowerModels.J1: An Open-Source Framework for Exploring Power Flow Formulations

By Carleton Coffrin, Russell W. Bent, K. Sundar, Yeesian Ng, Miles Lubin. Power Systems Computation Conference, 2017

303 citations recorded by the source corpus.

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.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/b74ba28ee3c90541d4d5ad8a328b4788d2ad3246

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

  1. Daniel D. Molzahn
  2. Carleton Coffrin
  3. Patrick Panciatici
  4. Juan Pablo Vielma
  5. B. Lesieutre
  6. Jean Maeght
  7. Christopher L. DeMarco
  8. Thomas J. Overbye

In Safety, Risk, Reliability and Quality

  1. Daniel D. Molzahn
  2. Thomas J. Overbye

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