Manage Standard Types

Show all Available Standard Types

pandapower.available_std_types(net, element='line')

Returns all standard types available for this network as a table.

Parameters:

Network (**net** - pandapower)
element (**element** - type of)

Returns:

typedata - table of standard type parameters

Create Standard Type

pandapower.create_std_type(net, data, name, element='line', overwrite=True, check_required=True)

Creates type data in the type database. The parameters that are used for the loadflow have to be at least contained in data. These parameters are:

c_nf_per_km, r_ohm_per_km, x_ohm_per_km and max_i_ka (for lines)

sn_mva, vn_hv_kv, vn_lv_kv, vk_percent, vkr_percent, pfe_kw, i0_percent, shift_degree* (for transformers)

sn_hv_mva, sn_mv_mva, sn_lv_mva, vn_hv_kv, vn_mv_kv, vn_lv_kv, vk_hv_percent, vk_mv_percent, vk_lv_percent,
vkr_hv_percent, vkr_mv_percent, vkr_lv_percent, pfe_kw, i0_percent, shift_mv_degree*, shift_lv_degree* (for 3-winding-transformers)

additional parameters can be added and later loaded into pandapower with the function “parameter_from_std_type”.

** only considered in loadflow if calculate_voltage_angles = True

The standard type is saved into the pandapower library of the given network by default.

Parameters:

network (**net** - The pandapower)
parameters (**data** - dictionary of standard type)
string (**name** - name of the standard type as)
"line" (**element** -)
"trafo3w" ("trafo" or)

EXAMPLE:

>>> line_data = {"c_nf_per_km": 0, "r_ohm_per_km": 0.642, "x_ohm_per_km": 0.083, "max_i_ka": 0.142, "type": "cs", "q_mm2": 50, "alpha": 4.03e-3}
>>> pandapower.create_std_type(net, line_data, "NAYY 4×50 SE", element='line')
>>> # Three phase line creation:
>>> pandapower.create_std_type(net, {"r_ohm_per_km": 0.1941, "x_ohm_per_km": 0.07476991,
                "c_nf_per_km": 1160., "max_i_ka": 0.421,
                "endtemp_degree": 70.0, "r0_ohm_per_km": 0.7766,
                "x0_ohm_per_km": 0.2990796,
                "c0_nf_per_km":  496.2}, name="unsymmetric_line_type",element = "line")
>>> # Three phase transformer creation
>>> pp.create_std_type(net, {"sn_mva": 1.6,
        "vn_hv_kv": 10,
        "vn_lv_kv": 0.4,
        "vk_percent": 6,
        "vkr_percent": 0.78125,
        "pfe_kw": 2.7,
        "i0_percent": 0.16875,
        "shift_degree": 0,
        "vector_group": vector_group,
        "tap_side": "lv",
        "tap_neutral": 0,
        "tap_min": -2,
        "tap_max": 2,
        "tap_step_degree": 0,
        "tap_step_percent": 2.5,
        "tap_changer_type": "Ratio",
        "vk0_percent": 6,
        "vkr0_percent": 0.78125,
        "mag0_percent": 100,
        "mag0_rx": 0.,
        "si0_hv_partial": 0.9,}, name='Unsymmetric_trafo_type', element="trafo")

pandapower.create_std_types(net, data, element='line', overwrite=True, check_required=True)

Creates multiple standard types in the type database.

Parameters:

network (**net** - The pandapower)
sets (**data** - dictionary of standard type parameter)
"line" (**element** -)
"line_dc"
"trafo3w" ("trafo" or)

EXAMPLE:

>>> linetypes = {"typ1": {"r_ohm_per_km": 0.01, "x_ohm_per_km": 0.02, "c_nf_per_km": 10, "max_i_ka": 0.4, "type": "cs"},
>>>              "typ2": {"r_ohm_per_km": 0.015, "x_ohm_per_km": 0.01, "c_nf_per_km": 30, "max_i_ka": 0.3, "type": "cs"}}
>>> pp.create_std_types(net, data=linetypes, element="line")

Adds zero sequence impedance parameters to net

pandapower.add_zero_impedance_parameters(net)

Adds all parameters required for zero sequence impedance calculations.

Parameters:

network (**net** - pandapower)
networks (zero sequence parameters of lines and transformers in pandapower)
std_type. (are entered using)
dataframe (This function adds them to the pandas)

Returns:

Now, net has all the zero sequence parameters

Copy Standard Types

pandapower.copy_std_types(to_net, from_net, element='line', overwrite=True)

Transfers all standard types of one network to another.

Parameters:

copied (**to_net** - The pandapower network to which the standard types are)
taken (**from_net** - The pandapower network from which the standard types are)
"trafo" (**element** - "line" or)
True (**overwrite** - if)
to_net (overwrites standard types which already exist in)

Load Standard Types

pandapower.load_std_type(net, name, element='line')

Loads standard type data from the linetypes database. Issues a warning if linetype is unknown.

Parameters:

network (**net** - The pandapower)
string (**name** - name of the standard type as)
"line" (**element** -)
"line_dc"
"trafo3w" ("trafo" or)

Returns:

typedata - dictionary containing type data

Check if Standard Type Exists

pandapower.std_type_exists(net, name, element='line')

Checks if a standard type exists.

Parameters:

Network (**net** - pandapower)
string (**name** - name of the standard type as)
element (**element** - type of)

Returns:

exists - True if standard type exists, False otherwise

Change Standard Type

pandapower.change_std_type(net, eid, name, element='line')

Changes the type of a given element in pandapower. Changes only parameter that are given for the type.

Parameters:

network (**net** - pandapower)
index (**eid** - element)
element (**element** - type of)
type (**name** - name of the new standard)

Load Additional Parameter from Library

pandapower.parameter_from_std_type(net, parameter, element='line', fill=None)

Loads standard types data for a parameter, which can be used to add an additional parameter, that is not included in the original pandapower datastructure but is available in the standard type database.

Parameters:

network (**net** - pandapower)
string (**parameter** - name of parameter as)
element (**element** - type of)
without (**fill** - fill-value that is assigned to all lines/trafos) – a value for the parameter, either because the line/trafo has no type or because the type does not have a value for the parameter

Example

>>> from pandapower import parameter_from_std_type
>>> from pandapower.networks import simple_mv_open_ring_net
>>>
>>> net = simple_mv_open_ring_net()
>>> parameter_from_std_type(net, "q_mm2")

Find Standard Type

pandapower.find_std_type_by_parameter(net, data, element='line', epsilon=0.)

Searches for a std_type that fits all values given in the data dictionary with the margin of epsilon.

Parameters:

network (**net** - pandapower)
parameters (**data** - dictionary of standard type)
element (**element** - type of)
comparison (**epsilon** - tolerance margin for parameter)

Returns:

fitting_types - list of fitting types or empty list

Delete Standard Type

pandapower.delete_std_type(net, name, element='line')

Deletes standard type parameters from database.

Parameters:

Network (**net** - pandapower)
string (**name** - name of the standard type as)
element (**element** - type of)