Spatial Configuration#

Configuring Spatial Scope#

PyPSA-USA allows for flexible configuration of the spatial scope of your energy model, enabling you to define the geographical area and level of detail for your simulations. The spatial scope is determined by the interconnect, model_topology configuration settings.

{interconnect} is used to select which of the three asynchronous interconnection to model. You can select western, eastern, texas, or usa to model the entire US.

After selecting your {interconnect}, you can specify model_topology: include: to filter individual states or balancing authorities to be selected in your model.

Example: Modeling California#

To create a model that includes only California, you can specify the relevant ReEDS zone IDs (p8-11) as shown below. This will limit the spatial scope to the specified regions within California. Your interconnect could be set to western or usa.

model_topology:
   include:
      reeds_zone: ['p8', 'p9', 'p10', 'p11']

Alternatively, you can use the code reeds_state: ‘CA’ option to achieve the same result by specifying the entire state.

In addition to filtering by reeds_zone and reeds_state, you can filter by reeds_ba, trans_reg, and nerc_reg shown graphically below.

Configuring Resource Resolution#

PyPSA-USA allows you to independently configure the resolution of resource zones from the transmission network. You can control this using the simpl and clusters parameters in the configuration file.

For example, if you want a transmission network with 10 nodes and a resource model with 100 nodes, you would configure it as follows:

scenario:
   clusters: [10m]
   simpl: [100]

This setup, using an m after the clusters wildcard, results in a model with 10 transmission nodes and 100 distinct renewable resource zones, allowing for more granular modeling of renewable resource distribution while keeping the transmission network simplified. If you use a c after the clusters wildcard, all conventional resources from the simpl step will not be clustered. If you input an a after the clusters wildcard, all resources will not be clustered beyond the simpl level.

Configuring Transmission Resolution#

Transmission Network Selection#

You can specify the transmission network you want to use by setting the model_topology: transmission_network: option. There are two available options:

‘reeds’: The ReEDS NARIS networks.
‘tamu’: The synthetic BE-TAMU nodal network.

When selecting between the three ReEDS NARIS networks, you will need to also specify the model_topology: topological_boundaries:. Currently you can set either county or reeds_zone. To use the FERC 1000 regions, you will need to use the custom network topologies described in the example below.

Transmission Network Resolution#

IF you are using the TAMU/BE network, you can flexibly set an arbitrary number of clusters between the min and max number of nodes. If using a ReEDS NARIS network, you need to specify the minimum number of clusters (nodes) for your modeled interconnection. The number of nodes for each zone is detailed in the table below.

If you’re working with custom configurations, PyPSA-USA will notify you during the cluster_network stage, indicating the correct number of nodes to set in the clusters configuration.

Spatial Scope	Reeds Zones	TAMU
	(Min Clusters)	(Max Clusters)
Western	34	4,919
Texas	7	1,338
Eastern	98	35,304
USA	132	41,561

Example: Meshed ReEDS NARIS WECC Topology#

If you would like to mesh the three ReEDS NARIS networks you can do so by using the model_topology: aggregate: option. For instance, to create a model where California is represented at a county level resolution, but Non-CA WECC areas are represented at the FERC 1000 level, you would configure the model as follows:

scenario:
   interconnect: [western]
   clusters: [87]
   simpl: [380] # can be set differently based on number of resource zones you'd like to keep


model_topology:
  transmission_network: 'reeds'
  topological_boundaries: 'county'
  interface_transmission_limits: false
  include:
    # nothing specified here since we are modeling the entire WECC
  aggregate:
    trans_grp: ['NorthernGrid_South', 'NorthernGrid_West', 'NorthernGrid_East', 'WestConnect_North','WestConnect_South']

This configuration will copper plate the Non-CA regions listed under trans_grp, effectively creating a copper-plate network where resources can be clustered and shared across the region. Using these custom aggregation requires information on the region memberships which you can find in workflow/repo_data/ReEDS_Constraints/membership.csv.

Spatial Configuration

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