Power grid research requires testing in realistic, large-scale, electric networks. However, in light of security threats, most information on the actual power grids is considered sensitive and therefore not available to the general public. So far, most power transmission studies have been carried using a few publicly available test grids. Still, these test grids are too small to capture the complexity of real grids. With this in mind, there has recently been a strong concentrated effort in developing methodologies for building realistic synthetic grids, based only on publicly available information. These synthetic grids are supposed to be based on some real example and to present analogous properties — such as geographic load/generation distribution, total load and generator types — while not actually presenting potentially sensitive information about the real grid.
This module provides an open source suite for generating synthetic grids based on real data openly available to the public. Power grids constructed via the SyntheticGrids module can be easily exported to pandapower for running optimum power flow calculations. Currently, information is limited to the USA region, but the framework can be readily applied to any other region, provided there are data sources available. We leverage the works published by Overbye's group and Soltan and Zussman, providing a direct implementation of their methods. For more details on the approaches adopted, please see Model.
- Birchfield, Adam B., et al. "Grid Structural Characteristics as Validation Criteria for Synthetic Networks." IEEE Transactions on Power Systems (2016).
- Gegner, Kathleen M., et al. "A methodology for the creation of geographically realistic synthetic power flow models." Power and Energy Conference at Illinois (PECI), 2016 IEEE. IEEE, 2016.
- Birchfield, Adam B., et al. "Statistical considerations in the creation of realistic synthetic power grids for geomagnetic disturbance studies." IEEE Transactions on Power Systems 32.2 (2017): 1502-1510.
- Soltan, Saleh, and Gil Zussman. "Generation of synthetic spatially embedded power grid networks." arXiv:1508.04447 [cs.SY], Aug. 2015.
- Implements basic types.
- Builds networks from real-world data.
- Builds connection topology from nodes.
- Builds transmission lines.
- Clusters nodes into substations.
- Provides basic checks for the graph structure.
- Interfaces with pandapower for exporting networks.
grid = Grid()
Create new (empty) grid
place_loads_from_zips!(grid, latitude limits, longitude limits)
Build load buses from zipcodes
place_gens_from_data!(grid, latitude limits, longitude limits)
Build generation buses from data (buses may also be placed manually)
Generate node connections
cluster!(grid, nloads, nboth, ngens)
Build substations by clustering nodes (optional)
Build transmission lines from connection topology
Exporting network to pandapower
This module makes use of
PyCall in order to interface with
pandapower. Since the reference charts in
pandapower do not contain transmission lines and transformer parameters for several voltages, currently, this module places all loads at 110kV and all generation at 380kV in order to have the proper parameters. Transformers are automatically placed every time two connected buses operate at different voltages. In order to obtain a
pandapower object from a SynGrid instance, simply run the command:
This returns a
PyObject. A path can be optionally passed as well in order to obtain a file saved in the native
pandapower format. These files can later be imported via the
- Note: the exported grid is zero-indexed, as it is being passed to Python routines.
- No type has been implemented for transformers.
- Connections between buses ignore differences in voltages.
- Transmission line properties are still oversimplified.
- There are missing quantities for AC OPF runs (DC should be fine).
- These limitations only pertain the SynGrids objects, not the grids exported to pandapower.
- Generator data has inconsistencies.
- 2015 survey data has 1337 power plants without any reported generator.
- 2014 survey data has 1403 power plants without any reported generator.
- There are unsited plants and plants with clearly wrong coordinates (the obvious ones were manually corrected).