def cluster_on_extra_high_voltage(network, busmap, with_time=True):
network_c = Network()
buses = aggregatebuses(network, busmap, {
'x': _leading(busmap, network.buses),
'y': _leading(busmap, network.buses)
})
# keep attached lines
lines = network.lines.copy()
mask = lines.bus0.isin(buses.index)
lines = lines.loc[mask, :]
# keep attached transformer
transformers = network.transformers.copy()
mask = transformers.bus0.isin(buses.index)
transformers = transformers.loc[mask, :]
io.import_components_from_dataframe(network_c, buses, "Bus")
io.import_components_from_dataframe(network_c, lines, "Line")
io.import_components_from_dataframe(network_c, transformers, "Transformer")
if with_time:
network_c.now = network.now
network_c.set_snapshots(network.snapshots)
# dealing with generators
network.generators['weight'] = 1
new_df, new_pnl = aggregategenerators(network, busmap, with_time)
io.import_components_from_dataframe(network_c, new_df, 'Generator')
for attr, df in iteritems(new_pnl):
io.import_series_from_dataframe(network_c, df, 'Generator', attr)
# dealing with all other components
aggregate_one_ports = components.one_port_components.copy()
aggregate_one_ports.discard('Generator')
for one_port in aggregate_one_ports:
new_df, new_pnl = aggregateoneport(network,
busmap,
component=one_port,
with_time=with_time)
io.import_components_from_dataframe(network_c, new_df, one_port)
for attr, df in iteritems(new_pnl):
io.import_series_from_dataframe(network_c, df, one_port, attr)
network_c.determine_network_topology()
return network_c
def cluster_on_extra_high_voltage(network, busmap, with_time=True):
""" Create a new clustered pypsa.Network given a busmap mapping all busids
to other busids of the same set.
Parameters
----------
network : pypsa.Network
Container for all network components.
busmap : dict
Maps old bus_ids to new bus_ids.
with_time : bool
If true time-varying data will also be aggregated.
Returns
-------
network : pypsa.Network
Container for all network components.
"""
network_c = Network()
buses = aggregatebuses(network, busmap, {
'x': _leading(busmap, network.buses),
'y': _leading(busmap, network.buses)
})
# keep attached lines
lines = network.lines.copy()
mask = lines.bus0.isin(buses.index)
lines = lines.loc[mask, :]
# keep attached transformer
transformers = network.transformers.copy()
mask = transformers.bus0.isin(buses.index)
transformers = transformers.loc[mask, :]
io.import_components_from_dataframe(network_c, buses, "Bus")
io.import_components_from_dataframe(network_c, lines, "Line")
io.import_components_from_dataframe(network_c, transformers, "Transformer")
if with_time:
network_c.snapshots = network.snapshots
network_c.set_snapshots(network.snapshots)
# dealing with generators
network.generators.control = "PV"
network.generators['weight'] = 1
new_df, new_pnl = aggregategenerators(network, busmap, with_time)
io.import_components_from_dataframe(network_c, new_df, 'Generator')
for attr, df in iteritems(new_pnl):
io.import_series_from_dataframe(network_c, df, 'Generator', attr)
# dealing with all other components
aggregate_one_ports = components.one_port_components.copy()
aggregate_one_ports.discard('Generator')
for one_port in aggregate_one_ports:
new_df, new_pnl = aggregateoneport(network,
busmap,
component=one_port,
with_time=with_time)
io.import_components_from_dataframe(network_c, new_df, one_port)
for attr, df in iteritems(new_pnl):
io.import_series_from_dataframe(network_c, df, one_port, attr)
network_c.determine_network_topology()
return network_c