PowerModelsDistribution.jl
PowerModelsDistribution.jl is an extention package of PowerModels.jl for Steady-State Power Distribution Network Optimization. It is designed to enable computational evaluation of emerging power network formulations and algorithms in a common platform. The code is engineered to decouple problem specifications (e.g. Power Flow, Optimal Power Flow, ...) from the power network formulations (e.g. AC, linear-approximation, SOC-relaxation, ...). This enables the definition of a wide variety of power network formulations and their comparison on common problem specifications.
Core Problem Specifications
- Power Flow (pf)
- ACP, ACR, IVR, LinDist3Flow, NFA, DCP
- Optimal Power Flow (opf)
- ACP, ACR, IVR, LinDist3Flow, NFA, DCP
- Continuous load shed, minimum load delta (mld)
- ACP, LinDist3Flow, NFA
- Optimal Power Flow with on-load tap-changer (opf_oltc)
- ACP
Note: The documentation is somewhat lagging behind development and the parings of network features with problem specifications with formulations has not been enumerated. We are working to correct this for you.
Core Network Formulations
- Nonlinear
- ACP
- ACR
- IVR
- Relaxations
- SDP BFM
- SOC BFM and BIM relaxation (W-space)
- Linear Approximations
- LinDist3Flow
- NFA
- DCP
Network Data Formats
- OpenDSS ".dss" files
Examples
Examples of how to use PowerModelsDistribution can be found in the main documentation and in Jupyter Notebooks inside the /examples
directory
Development
Community-driven development and enhancement of PowerModelsDistribution are welcome and encouraged. Please fork this repository and share your contributions to the master with pull requests.
Acknowledgments
This code has been developed as part of the Advanced Network Science Initiative at Los Alamos National Laboratory. The primary developers are David Fobes(@pseudocubic) and Carleton Coffrin(@ccoffrin) with support from the following contributors:
- Sander Claeys (@sanderclaeys) KU Leuven, transformer models and ACR formulation
- Frederik Geth (@frederikgeth) CSIRO, Distribution modeling advise
Citing PowerModelsDistribution
If you find PowerModelsDistribution useful for your work, we kindly request that you cite the following publication:
@misc{fobes2020powermodelsdistributionjl,
title={PowerModelsDistribution.jl: An Open-Source Framework for Exploring Distribution Power Flow Formulations},
author={David M Fobes and Sander Claeys and Frederik Geth and Carleton Coffrin},
year={2020},
eprint={2004.10081},
archivePrefix={arXiv},
primaryClass={cs.CE}
}
License
This code is provided under a BSD license as part of the Multi-Infrastructure Control and Optimization Toolkit (MICOT) project, LA-CC-13-108.