PowerModelsDistribution.jl

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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 https://arxiv.org/abs/2004.10081:

@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.

linyunfeng201203 / PowerModelsDistribution.jl