Topological Searches¶
Once you converted your network into a MultiGraph there are several functions to perform topological searches and analyses at your disposal. You can either use the general-purpose functions that come with NetworkX (see http:/networkx.github.io/documentation/networkx-1.10/reference/algorithms.html) or topology’s own ones which are specialized on electrical networks.
calc_distance_to_bus¶
- pandapower.topology.calc_distance_to_bus(net, bus, respect_switches=True, nogobuses=None, notravbuses=None, weight='weight')¶
Calculates the shortest distance between a source bus and all buses connected to it.
- INPUT:
net (pandapowerNet) - Variable that contains a pandapower network.
bus (integer) - Index of the source bus.
- OPTIONAL:
- respect_switches (boolean, True) - True: open line switches are being considered
(no edge between nodes)
False: open line switches are being ignored
nogobuses (integer/list, None) - nogobuses are not being considered
- notravbuses (integer/list, None) - lines connected to these buses are not being
considered
weight (string, None) – Edge data key corresponding to the edge weight
- OUTPUT:
- dist - Returns a pandas series with containing all distances to the source bus
in km. If weight=None dist is the topological distance (int).
- EXAMPLE:
import pandapower.topology as top
dist = top.calc_distance_to_bus(net, 5)
connected_component¶
- pandapower.topology.connected_component(mg, bus, notravbuses=[])¶
Finds all buses in a NetworkX graph that are connected to a certain bus.
- INPUT:
mg (NetworkX graph) - NetworkX Graph or MultiGraph that represents a pandapower network.
bus (integer) - Index of the bus at which the search for connected components originates
- OPTIONAL:
- notravbuses (list/set) - indices of notravbuses: lines connected to these buses are
not being considered in the graph
- OUTPUT:
cc (generator) - Returns a generator that yields all buses connected to the input bus
- EXAMPLE:
import pandapower.topology as top
mg = top.create_nxgraph(net)
cc = top.connected_component(mg, 5)
connected_components¶
- pandapower.topology.connected_components(mg, notravbuses={})¶
Clusters all buses in a NetworkX graph that are connected to each other.
- INPUT:
mg (NetworkX graph) - NetworkX Graph or MultiGraph that represents a pandapower network.
OPTIONAL: notravbuses (set) - Indices of notravbuses: lines connected to these buses are
not being considered in the graph
- OUTPUT:
- cc (generator) - Returns a generator that yields all clusters of buses connected
to each other.
- EXAMPLE:
import pandapower.topology as top
mg = top.create_nxgraph(net)
cc = top.connected_components(net, 5)
unsupplied_buses¶
- pandapower.topology.unsupplied_buses(net, mg=None, slacks=None, respect_switches=True)¶
Finds buses, that are not connected to an external grid.
- INPUT:
net (pandapowerNet) - variable that contains a pandapower network
- OPTIONAL:
mg (NetworkX graph) - NetworkX Graph or MultiGraph that represents a pandapower network.
- in_service_only (boolean, False) - Defines whether only in service buses should be
included in unsupplied_buses.
- slacks (set, None) - buses which are considered as root / slack buses. If None, all
existing slack buses are considered.
- respect_switches (boolean, True) - Fixes how to consider switches - only in case of no
given mg.
- OUTPUT:
ub (set) - unsupplied buses
- EXAMPLE:
import pandapower.topology as top
top.unsupplied_buses(net)
determine_stubs¶
- pandapower.topology.determine_stubs(net, roots=None, mg=None, respect_switches=False)¶
Finds stubs in a network. Open switches are being ignored. Results are being written in a new column in the bus table (“on_stub”) and line table (“is_stub”) as True/False value.
- INPUT:
net (pandapowerNet) - Variable that contains a pandapower network.
- OPTIONAL:
- roots (integer/list, None) - indices of buses that should be excluded (by default, the
ext_grid buses will be set as roots)
- EXAMPLE:
import pandapower.topology as top
top.determine_stubs(net, roots = [0, 1])