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)¶ - 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
- OUTPUT:
- dist - Returns a pandas series with containing all distances to the source bus
- in km.
- 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) - Indeces 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_nx_graph(net)
cc = top.connected_component(mg, 5)
connected_components¶
-
pandapower.topology.
connected_components
(mg, notravbuses=set([]))¶ 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_nx_graph(net)
cc = top.connected_components(net, 5)
unsupplied_buses¶
-
pandapower.topology.
unsupplied_buses
(net, mg=None, in_service_only=False, 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) - Indeces 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])