Primary tabs

Pacific Northwest National Laboratory

Pacific Northwest National Laboratory (PNNL) and its power industry and software vendor partners are developing an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning.

The SDET approach will uniquely 1) derive features and metrics for both transmission and distribution (T&D) systems by analyzing many public and private datasets provided by our industry partners National Rural Electric Cooperative Association (NRECA), PJM Interconnection (PJM), California Independent System Operator (CAISO), and Avista Utilities (Avista); 2) develop data-creation tools and use these tools to generate large-scale open-access realistic datasets that comply with the metrics for both T&D systems, and 3) validate the created datasets using industry tools provided by our vendor partner General Electric (GE).

License

Other (Public Domain)

Other Access

The information on this page (the dataset metadata) is also available in these formats.

JSON RDF

via the DKAN API

DOI Information

No DOI assigned at this time.

SDET topology generation tool

The SDET power grid topology generation tool generates the topology for a synthetic power grid transmission model by selecting and combining a bunch of fragments from real power grid models. This tool is tested under Linux environment.

Simply unzip the .zip file to any directory. To run the program, you need:

(1) Rebuild the Hungarian module in the sub-directory: /hungarian-master. Please follow the instructions under //hungarian-master/README.md to build the module.

(2) The main file to run the tool is SDET.py. Simple modify line 31, to put the number of buses for the power grid model you want to generate (currently it is 1000), and then you can directly run it with python.

(3) The sub-directory /Fragments includes many fragments from the public available systems. These fragments are the “building blocks” for the synthetic power grid model topology generation. You can also add other fragments with the SDET fragment creation tools for your own system and put them in this subfolder. Currently we provide the fragments from the following public available systems: European system [1], Great Britian system [2], Polish system [3], and synthetic power grid models developed by Professor Thomas Overbye from Texas A&M University [4]. Here we express our sincere thanks to all the authors of these publicly available data-sets for allowing us to use them.

(4) The sub-directory /Results includes the output results from this tool. After running the SDET.py, the tool will give a PTI RAW format power flow case representing the topology of the synthetic model. Note that this power flow case does not have a converged power flow yet, you need to run the “SDET_generate_basecse_tool”, which takes this PTI RAW file as input, to get a converged power flow. The txt file in this sub- directory gives the information of how many fragments in the sub- directory /Fragments are used to create the synthetic power grid model and the names of the used fragments. Other pdf files generated in this sub- directory include a set of statistics of the graphic properties of the generated synthetic power grid model topology.

For any questions regarding this tool, please contact Dr. Stephen Young at PNNL: stephen.young@pnnl.gov

[1] S. Fliscounakis, P. Panciatici, F. Capitanescu, and L. Wehenkel, "Contingency ranking with respect to overloads in very large power systems taking into account uncertainty, preventive and corrective actions", Power Systems, IEEE Trans. on, (28)4:4909-4917, 2013.
[2] https://www.maths.ed.ac.uk/optenergy/NetworkData/fullGB/
[3] MATPOWER http://www.pserc.cornell.edu/matpower/
[4] https://electricgrids.engr.tamu.edu/

Data and Resources

FieldValue
Publisher
Modified
2019-10-01
Release Date
2019-03-19
Identifier
5e9bd078-7b36-41a7-9887-e74b0aaaf644
License
Other (Public Domain)
Author
Renke Huang
Contact Name
Renke Huang
Contact Email
Public Access Level
Public