pypowsybl.network.Network.get_2_windings_transformers

Network.get_2_windings_transformers(all_attributes=False, attributes=None, **kwargs)[source]

Get a dataframe of 2 windings transformers.

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:

A dataframe of 2 windings transformers.

Return type:

DataFrame

Notes

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

  • r: the resistance of the transformer at its “2” side (in Ohm)

  • x: the reactance of the transformer at its “2” side (in Ohm)

  • b: the susceptance of transformer at its “2” side (in Siemens)

  • g: the conductance of transformer at its “2” side (in Siemens)

  • rated_u1: the rated voltage of the transformer at side 1 (in kV)

  • rated_u2: the rated voltage of the transformer at side 2 (in kV)

  • rated_s: the rated apparent power of the transformer (in MVA)

  • p1: the active flow on the transformer at its “1” side, NaN if no loadflow has been computed (in MW)

  • q1: the reactive flow on the transformer at its “1” side, NaN if no loadflow has been computed (in MVAr)

  • i1: the current on the transformer at its “1” side, NaN if no loadflow has been computed (in A)

  • p2: the active flow on the transformer at its “2” side, NaN if no loadflow has been computed (in MW)

  • q2: the reactive flow on the transformer at its “2” side, NaN if no loadflow has been computed (in MVAr)

  • i2: the current on the transformer at its “2” side, NaN if no loadflow has been computed (in A)

  • voltage_level1_id: voltage level where the transformer is connected, on side 1

  • voltage_level2_id: voltage level where the transformer is connected, on side 2

  • bus1_id: bus where this transformer is connected, on side 1

  • bus2_id: bus where this transformer is connected, on side 2

  • bus_breaker_bus1_id (optional): bus of the bus-breaker view where this transformer is connected, on side 1

  • bus_breaker_bus2_id (optional): bus of the bus-breaker view where this transformer is connected, on side 2

  • node1 (optional): node where this transformer is connected on side 1, in node-breaker voltage levels

  • node2 (optional): node where this transformer is connected on side 2, in node-breaker voltage levels

  • connected1: True if the side “1” of the transformer is connected to a bus

  • connected2: True if the side “2” of the transformer is connected to a bus

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

  • selected_limits_group_1 (optional): Name of the selected operational limits group selected for side 1

  • selected_limits_group_2 (optional): Name of the selected operational limits group selected for side 2

  • rho (optional): the voltage ratio of the transformer at current tap position

  • alpha (optional): the phase shift of the transformer at current tap position (in degree)

  • r_at_current_tap (optional): the resistance of the transformer at current tap position (in Ohm)

  • x_at_current_tap (optional): the reactance of the transformer at current tap position (in Ohm)

  • g_at_current_tap (optional): the susceptance of the transformer at current tap position (in Ohm)

  • b_at_current_tap (optional): the conductance of the transformer at current tap position (in Ohm)

This dataframe is indexed by the id of the two windings transformers

Examples

net = pp.network.create_ieee14()
net.get_2_windings_transformers()

will output something like:

r

x

g

b

rated_u1

rated_u2

rated_s

p1

q1

i1

p2

q2

i2

voltage_level1_id

voltage_level2_id

bus1_id

bus2_id

connected1

connected2

id

T4-7-1

0.0

0.409875

0.0

0.0

132.030

14.0

NaN

NaN

NaN

NaN

NaN

NaN

NaN

VL4

VL7

VL4_0

VL7_0

True

True

T4-9-1

0.0

0.800899

0.0

0.0

130.815

12.0

NaN

NaN

NaN

NaN

NaN

NaN

NaN

VL4

VL9

VL4_0

VL9_0

True

True

T5-6-1

0.0

0.362909

0.0

0.0

125.820

12.0

NaN

NaN

NaN

NaN

NaN

NaN

NaN

VL5

VL6

VL5_0

VL6_0

True

True

 
net = pp.network.create_ieee14()
net.get_2_windings_transformers(all_attributes=True)

will output something like:

r

x

g

b

rated_u1

rated_u2

rated_s

p1

q1

i1

p2

q2

i2

voltage_level1_id

voltage_level2_id

bus1_id

bus2_id

connected1

connected2

id

T4-7-1

0.0

0.409875

0.0

0.0

132.030

14.0

NaN

NaN

NaN

NaN

NaN

NaN

NaN

VL4

VL7

VL4_0

VL7_0

True

True

T4-9-1

0.0

0.800899

0.0

0.0

130.815

12.0

NaN

NaN

NaN

NaN

NaN

NaN

NaN

VL4

VL9

VL4_0

VL9_0

True

True

T5-6-1

0.0

0.362909

0.0

0.0

125.820

12.0

NaN

NaN

NaN

NaN

NaN

NaN

NaN

VL5

VL6

VL5_0

VL6_0

True

True

 
net = pp.network.create_ieee14()
net.get_2_windings_transformers(attributes=['p1','q1','i1','p2','q2','i2','voltage_level1_id','voltage_level2_id','bus1_id','bus2_id','connected1','connected2'])

will output something like:

p1

q1

i1

p2

q2

i2

voltage_level1_id

voltage_level2_id

bus1_id

bus2_id

connected1

connected2

id

T4-7-1

NaN

NaN

NaN

NaN

NaN

NaN

VL4

VL7

VL4_0

VL7_0

True

True

T4-9-1

NaN

NaN

NaN

NaN

NaN

NaN

VL4

VL9

VL4_0

VL9_0

True

True

T5-6-1

NaN

NaN

NaN

NaN

NaN

NaN

VL5

VL6

VL5_0

VL6_0

True

True