A PowerModelsRestoration provides extensions to PowerModels for solving the power system restoration tasks. A core building block in PowerModelsRestoration is the Maximum Load Delivery (MLD) problem, which provides a reliable numerical method for solving challenging N-k damage scenarios, such as those that arise in the analysis of extreme events.
- Restoration Ordering Problem (rop)
- Minimum Restoration Set Problem (mrsp)
- Forward Restoration Redispatch
- Maximum Load Delivery with Discrete Variables (mld_uc)
- Maximum Load Delivery with Continuous Variables (mld)
- AC (polar coordinates)
- DC Approximation (polar coordinates)
- SOC Relaxation (W-space)
- SDP Relaxation (W-space)
If you find the PowerModelsRestoration package useful in your work, we request that you cite the following publication:
@inproceedings{rhodes2020powermodelsrestoration,
author = {Rhodes, Noah and Fobes, David M and Coffrin, Carleton and Roald, Line},
title = {PowerModelsRestoration.jl: An open-source framework for exploring power network restoration algorithms},
booktitle = {2020 Power Systems Computation Conference (PSCC)},
year = {2020},
month = {June},
doi = {10.1016/j.epsr.2020.106736}
}
In addition, if the MLD problem from PowerModelsRestoration useful in your work, we kindly request that you cite the following publication:
@article{8494809,
author={Carleton Coffrin and Russell Bent and Byron Tasseff and Kaarthik Sundar and Scott Backhaus},
title={Relaxations of AC Maximal Load Delivery for Severe Contingency Analysis},
journal={IEEE Transactions on Power Systems},
volume={34}, number={2}, pages={1450-1458},
month={March}, year={2019},
doi={10.1109/TPWRS.2018.2876507}, ISSN={0885-8950}
}
If you use the RRR problem in your work, we kindly request that you cite the folloring publication
@inproceedings{rhodes2022recursive,
author = {Rhodes, Noah and Coffrin, Carleton and Roald, Line},
title = {Recursive restoration refinement: A fast heuristic for near-optimal restoration prioritization in power systems},
booktitle = {2022 Power Systems Computation Conference (PSCC)},
year = {2022},
month = {June},
doi = {10.1016/j.epsr.2022.108454}
}
Citation of the PowerModels framework is also encouraged when publishing works that use PowerModels extension packages.
This code is provided under a BSD license as part of the Multi-Infrastructure Control and Optimization Toolkit (MICOT) project, C15024.