Unbalanced Power Flow Optimization with PowerModelsDistribution

07/29/2021, 1:00 PM1:10 PM UTC


With the recent advancements in power distribution, e.g., higher penetration of distributed energy resources (DERs), there is a significant demand for optimization tools to solve a variety of complex operational and planning problems, such as optimal dispatch, load shedding, and on-load tap changing. We have developed an optimization-focused approach to phase unbalanced power distribution modeling called PowerModelsDistribution, the design and usage of which we will introduce in this talk.


PowerModelsDistribution (PMD) is an optimization focused toolkit for power distribution networks modeling, designed using JuMP, which allows for a decoupling of the various problems, power flow formulations, and optimization solvers, for easy exploration and application of a variety of power flow problem types and mathematical formulations related to multi-phase quasi-steady-state optimization. PMD includes several nonlinear AC formulations, linear approximations, and relaxations, all based on state-of-the-art peer-reviewed research, and has native support for both single-period and multi-period (time series) problems, the latter of which is especially relevant due to the larger number of energy storage components appearing in power distribution networks. PMD includes a native Julia OpenDSS data format parser, allowing us to validate the results of AC power flow against OpenDSS using a number of IEEE distribution test feeders, and provides a simple avenue to support existing data models for a broad collection of distribution system components such as photovoltaic systems and energy storage.

Platinum sponsors

Julia Computing

Gold sponsors

Relational AI

Silver sponsors

Invenia LabsConningPumas AIQuEra Computing Inc.King Abdullah University of Science and TechnologyDataChef.coJeffrey Sarnoff

Media partners

Packt Publication

Fiscal Sponsor