pypowsybl.network.Network.get_generators

Network.get_generators(all_attributes=False, attributes=None, **kwargs)

Get a dataframe of generators.

Parameters:

• all_attributes (bool) – flag for including all attributes in the dataframe, default is false

• attributes (List[str] | None) – attributes to include in the dataframe. The 2 parameters are mutually exclusive. If no parameter is specified, the dataframe will include the default attributes.

• kwargs (Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]) – the data to be selected, as named arguments.

Returns:

the generators dataframe.

Return type:

DataFrame

Notes

The resulting dataframe, depending on the parameters, will include the following columns:

• energy_source: the energy source used to fuel the generator

• target_p: the target active value for the generator (in MW)

• max_p: the maximum active value for the generator (MW)

• min_p: the minimum active value for the generator (MW)

• max_q: the maximum reactive value for the generator only if reactive_limits_kind is MIN_MAX (MVar)

• min_q: the minimum reactive value for the generator only if reactive_limits_kind is MIN_MAX (MVar)

• max_q_at_target_p (optional): the maximum reactive value for the generator for the target p specified (MVar)

• min_q_at_target_p (optional): the minimum reactive value for the generator for the target p specified (MVar)

• max_q_at_p (optional): the maximum reactive value for the generator at current p (MVar)

• min_q_at_p (optional): the minimum reactive value for the generator at current p (MVar)

• rated_s: The rated nominal power (MVA)

• reactive_limits_kind: type of the reactive limit of the generator (can be MIN_MAX, CURVE or NONE)

• target_v: the target voltage magnitude value for the generator (in kV)

• equivalent_local_target_v (optional): a local target voltage value expected to be consistent with the remote target voltage (in kV)

  (to be used by simulators that deactivate the remote voltage algorithms, or by dynamic simulators that use this voltage as a starting value)

• target_q: the target reactive value for the generator (in MVAr)

• voltage_regulator_on: True if the generator regulates voltage

• regulated_element_id: the ID of the network element where voltage is regulated

• regulated_bus_id: the ID of the bus from bus view where voltage is regulated

• regulated_bus_breaker_bus_id: the ID of the bus from bus/breaker view where voltage is regulated

• p: the actual active production of the generator (NaN if no loadflow has been computed)

• q: the actual reactive production of the generator (NaN if no loadflow has been computed)

• i: the current on the generator, NaN if no loadflow has been computed (in A)

• voltage_level_id: at which substation this generator is connected

• bus_id: bus where this generator is connected

• bus_breaker_bus_id (optional): bus of the bus-breaker view where this generator is connected

• node (optional): node where this generator is connected, in node-breaker voltage levels

• condenser (optional): True if the generator is a condenser

• connected: True if the generator is connected to a bus

• fictitious (optional): True if the generator is part of the model and not of the actual network

This dataframe is indexed on the generator ID.

Examples

net = pp.network.create_ieee14()
net.get_generators()

will output something like:

	energy_source	target_p	max_p	min_p	target_v	target_q	voltage_regulator_on	p	q	voltage_level_id	bus_id
id
B1-G	OTHER	232.4	9999.0	-9999.0	1.060	-16.9	True	NaN	NaN	VL1	VL1_0
B2-G	OTHER	40.0	9999.0	-9999.0	1.045	42.4	True	NaN	NaN	VL2	VL2_0
B3-G	OTHER	0.0	9999.0	-9999.0	1.010	23.4	True	NaN	NaN	VL3	VL3_0
B6-G	OTHER	0.0	9999.0	-9999.0	1.070	12.2	True	NaN	NaN	VL6	VL6_0
B8-G	OTHER	0.0	9999.0	-9999.0	1.090	17.4	True	NaN	NaN	VL8	VL8_0

net = pp.network.create_ieee14()
net.get_generators(all_attributes=True)

will output something like:

	energy_source	target_p	max_p	min_p	target_v	target_q	voltage_regulator_on	p	q	voltage_level_id	bus_id
id
B1-G	OTHER	232.4	9999.0	-9999.0	1.060	-16.9	True	NaN	NaN	VL1	VL1_0
B2-G	OTHER	40.0	9999.0	-9999.0	1.045	42.4	True	NaN	NaN	VL2	VL2_0
B3-G	OTHER	0.0	9999.0	-9999.0	1.010	23.4	True	NaN	NaN	VL3	VL3_0
B6-G	OTHER	0.0	9999.0	-9999.0	1.070	12.2	True	NaN	NaN	VL6	VL6_0
B8-G	OTHER	0.0	9999.0	-9999.0	1.090	17.4	True	NaN	NaN	VL8	VL8_0

net = pp.network.create_ieee14()
net.get_generators(attributes=['energy_source','target_p','max_p','min_p','p','voltage_level_id','bus_id'])

will output something like:

	energy_source	target_p	max_p	min_p	p	voltage_level_id	bus_id
id
B1-G	OTHER	232.4	9999.0	-9999.0	NaN	VL1	VL1_0
B2-G	OTHER	40.0	9999.0	-9999.0	NaN	VL2	VL2_0
B3-G	OTHER	0.0	9999.0	-9999.0	NaN	VL3	VL3_0
B6-G	OTHER	0.0	9999.0	-9999.0	NaN	VL6	VL6_0
B8-G	OTHER	0.0	9999.0	-9999.0	NaN	VL8	VL8_0

Warning

The “generator convention” is used for the “input” columns (target_p, max_p, min_p, target_v and target_q) while the “load convention” is used for the ouput columns (p and q).

Most of the time, this means that p and target_p will have opposite sign. This also entails that p can be lower than min_p. Actually, the relation: \(\\text{min_p} <= -p <= \\text{max_p}\) should hold.