Linearized Distribution Optimal Power Flow for OEDI SI
This research is to meant to demonstrate the OEDI SI use case for distributed optimal power flow (DOPF). The goal was to formulate the optimal power flow problem in the distribution system for active and reactive power setpoints of PV systems using topology information and voltage measurements. The co-simulation runs every 15 minutes as outlined within the scenario file for the given feeder configuration.
The linked GitHub repository includes five federates to achieve DOPF for the small, medium, large, and IEEE 123 feeder scenarios. We are using the OEDI SI framework, as well as the example feeder, sensor, recorder, and estimator federates provided in the example repository for OEDI SI. We also provide a runner script for switching between scenarios.
Citation Formats
TY - DATA
AB - This research is to meant to demonstrate the OEDI SI use case for distributed optimal power flow (DOPF). The goal was to formulate the optimal power flow problem in the distribution system for active and reactive power setpoints of PV systems using topology information and voltage measurements. The co-simulation runs every 15 minutes as outlined within the scenario file for the given feeder configuration.
The linked GitHub repository includes five federates to achieve DOPF for the small, medium, large, and IEEE 123 feeder scenarios. We are using the OEDI SI framework, as well as the example feeder, sensor, recorder, and estimator federates provided in the example repository for OEDI SI. We also provide a runner script for switching between scenarios.
AU - Sadnan, Rabayet
A2 - Poudel, Shiva
A3 - Mckinsey, Joseph
A4 - Slay, Tylor
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.25984/2202772
KW - energy
KW - power
KW - optimal power flow
KW - distribution
KW - PV
KW - simulation
KW - linearized distribution
KW - power flow
KW - grid
KW - DOPF
KW - oedi si
KW - solar
KW - solar power
KW - code
KW - algorithm
KW - python
LA - English
DA - 2023/10/03
PY - 2023
PB - Pacific Northwest National Laboratory
T1 - Linearized Distribution Optimal Power Flow for OEDI SI
UR - https://doi.org/10.25984/2202772
ER -
Sadnan, Rabayet, et al. Linearized Distribution Optimal Power Flow for OEDI SI. Pacific Northwest National Laboratory, 3 October, 2023, Open Energy Data Initiative (OEDI). https://doi.org/10.25984/2202772.
Sadnan, R., Poudel, S., Mckinsey, J., & Slay, T. (2023). Linearized Distribution Optimal Power Flow for OEDI SI. [Data set]. Open Energy Data Initiative (OEDI). Pacific Northwest National Laboratory. https://doi.org/10.25984/2202772
Sadnan, Rabayet, Shiva Poudel, Joseph Mckinsey, and Tylor Slay. Linearized Distribution Optimal Power Flow for OEDI SI. Pacific Northwest National Laboratory, October, 3, 2023. Distributed by Open Energy Data Initiative (OEDI). https://doi.org/10.25984/2202772
@misc{OEDI_Dataset_5972,
title = {Linearized Distribution Optimal Power Flow for OEDI SI},
author = {Sadnan, Rabayet and Poudel, Shiva and Mckinsey, Joseph and Slay, Tylor},
abstractNote = {This research is to meant to demonstrate the OEDI SI use case for distributed optimal power flow (DOPF). The goal was to formulate the optimal power flow problem in the distribution system for active and reactive power setpoints of PV systems using topology information and voltage measurements. The co-simulation runs every 15 minutes as outlined within the scenario file for the given feeder configuration.
The linked GitHub repository includes five federates to achieve DOPF for the small, medium, large, and IEEE 123 feeder scenarios. We are using the OEDI SI framework, as well as the example feeder, sensor, recorder, and estimator federates provided in the example repository for OEDI SI. We also provide a runner script for switching between scenarios.},
url = {https://data.openei.org/submissions/5972},
year = {2023},
howpublished = {Open Energy Data Initiative (OEDI), Pacific Northwest National Laboratory, https://doi.org/10.25984/2202772},
note = {Accessed: 2025-04-25},
doi = {10.25984/2202772}
}
https://dx.doi.org/10.25984/2202772
Details
Data from Oct 3, 2023
Last updated Oct 19, 2023
Submitted Oct 3, 2023
Organization
Pacific Northwest National Laboratory
Contact
Tylor Slay
971.331.5962
Authors
Research Areas
Keywords
energy, power, optimal power flow, distribution, PV, simulation, linearized distribution, power flow, grid, DOPF, oedi si, solar, solar power, code, algorithm, pythonDOE Project Details
Project Name SETO OEDI Data & Analytics Library
Project Number EE0054321
