Transformer with non-trivial phase shift and tap ratio

This example is a copy of pandapower’s minimal example.

[1]:

import pypsa
import numpy as np
import pandas as pd

[2]:

network = pypsa.Network()

network.add("Bus","MV bus",v_nom=20, v_mag_pu_set=1.02)
network.add("Bus","LV1 bus",v_nom=.4)
network.add("Bus","LV2 bus",v_nom=.4)

network.add("Transformer", "MV-LV trafo", type="0.4 MVA 20/0.4 kV", bus0="MV bus", bus1="LV1 bus")
network.add("Line", "LV cable", type="NAYY 4x50 SE",bus0="LV1 bus", bus1="LV2 bus", length=0.1)
network.add("Generator", "External Grid", bus="MV bus", control="Slack")
network.add("Load", "LV load", bus="LV2 bus", p_set=0.1, q_set=0.05)

[3]:

def run_pf():
    network.lpf()
    network.pf(use_seed=True)
    return pd.DataFrame({'Voltage Angles': network.buses_t.v_ang.loc['now']*180./np.pi,
                        'Volate Magnitude': network.buses_t.v_mag_pu.loc['now']})

[4]:

run_pf()

INFO:pypsa.pf:Performing linear load-flow on AC sub-network SubNetwork 0 for snapshot(s) Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Performing non-linear load-flow on AC sub-network SubNetwork 0 for snapshots Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Newton-Raphson solved in 3 iterations with error of 0.000000 in 0.021245 seconds

[4]:

	Voltage Angles	Volate Magnitude
Bus
MV bus	0.000000	1.020000
LV1 bus	-150.760126	1.008843
LV2 bus	-149.884141	0.964431

[5]:

network.transformers.tap_position = 2
run_pf()

INFO:pypsa.pf:Performing linear load-flow on AC sub-network SubNetwork 0 for snapshot(s) Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Performing non-linear load-flow on AC sub-network SubNetwork 0 for snapshots Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Newton-Raphson solved in 3 iterations with error of 0.000000 in 0.022213 seconds

[5]:

	Voltage Angles	Volate Magnitude
Bus
MV bus	0.000000	1.020000
LV1 bus	-150.843911	0.959655
LV2 bus	-149.870837	0.912713

[6]:

network.transformers.tap_position = -2
run_pf()

INFO:pypsa.pf:Performing linear load-flow on AC sub-network SubNetwork 0 for snapshot(s) Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Performing non-linear load-flow on AC sub-network SubNetwork 0 for snapshots Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Newton-Raphson solved in 3 iterations with error of 0.000000 in 0.022197 seconds

[6]:

	Voltage Angles	Volate Magnitude
Bus
MV bus	0.000000	1.020000
LV1 bus	-150.681666	1.063133
LV2 bus	-149.896634	1.021202

Now play with tap changer on LV side

[7]:

new_trafo_lv_tap = network.transformer_types.loc[["0.4 MVA 20/0.4 kV"]]
new_trafo_lv_tap.index = ["New trafo"]
new_trafo_lv_tap.tap_side = 1
new_trafo_lv_tap.T

[7]:

	New trafo
f_nom	50.0
s_nom	0.4
v_nom_0	20.0
v_nom_1	0.4
vsc	6.0
vscr	1.425
pfe	1.35
i0	0.3375
phase_shift	150.0
tap_side	1
tap_neutral	0
tap_min	-2
tap_max	2
tap_step	2.5
references	pandapower;Oswald - Transformatoren - Vorlesun...

[8]:

network.transformer_types = network.transformer_types.append(new_trafo_lv_tap)
network.transformers.type = "New trafo"
network.transformers.tap_position = 2
run_pf()

/tmp/ipykernel_4978/2416978983.py:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  network.transformer_types = network.transformer_types.append(new_trafo_lv_tap)
INFO:pypsa.pf:Performing linear load-flow on AC sub-network SubNetwork 0 for snapshot(s) Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Performing non-linear load-flow on AC sub-network SubNetwork 0 for snapshots Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Newton-Raphson solved in 3 iterations with error of 0.000000 in 0.021798 seconds

[8]:

	Voltage Angles	Volate Magnitude
Bus
MV bus	0.000000	1.020000
LV1 bus	-150.755820	1.059317
LV2 bus	-149.964875	1.017221

[9]:

network.transformers.T

[9]:

Transformer	MV-LV trafo
attribute
bus0	MV bus
bus1	LV1 bus
type	New trafo
model	t
x	0.058283
r	0.01425
g	0.003375
b	-0.0
s_nom	0.4
s_nom_extendable	False
s_nom_min	0.0
s_nom_max	inf
s_max_pu	1.0
capital_cost	0.0
num_parallel	1.0
tap_ratio	1.05
tap_side	1
tap_position	2
phase_shift	150.0
build_year	0
lifetime	inf
v_ang_min	-inf
v_ang_max	inf
sub_network	0
x_pu	0.145712
r_pu	0.035618
g_pu	0.00135
b_pu	-0.0
x_pu_eff	0.152994
r_pu_eff	0.037406
s_nom_opt	0.0

[10]:

network.transformers.tap_position = -2
run_pf()

INFO:pypsa.pf:Performing linear load-flow on AC sub-network SubNetwork 0 for snapshot(s) Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Performing non-linear load-flow on AC sub-network SubNetwork 0 for snapshots Index(['now'], dtype='object', name='snapshot')
INFO:pypsa.pf:Newton-Raphson solved in 3 iterations with error of 0.000000 in 0.022144 seconds

[10]:

	Voltage Angles	Volate Magnitude
Bus
MV bus	0.000000	1.020000
LV1 bus	-150.765232	0.958366
LV2 bus	-149.789394	0.911353

Now make sure that the phase shift is also there in the LOPF

[11]:

network.generators.p_nom = 1.
network.lines.s_nom = 1.
network.lopf()
pd.DataFrame({'Voltage Angles': network.buses_t.v_ang.loc['now']*180./np.pi,
                        'Volate Magnitude': network.buses_t.v_mag_pu.loc['now']})

INFO:pypsa.opf:Performed preliminary steps
INFO:pypsa.opf:Building pyomo model using `kirchhoff` formulation
INFO:pypsa.opf:Solving model using glpk
INFO:pypsa.opf:Optimization successful

# ==========================================================
# = Solver Results                                         =
# ==========================================================
# ----------------------------------------------------------
#   Problem Information
# ----------------------------------------------------------
Problem:
- Name: unknown
  Lower bound: 0.0
  Upper bound: 0.0
  Number of objectives: 1
  Number of constraints: 8
  Number of variables: 4
  Number of nonzeros: 10
  Sense: minimize
# ----------------------------------------------------------
#   Solver Information
# ----------------------------------------------------------
Solver:
- Status: ok
  Termination condition: optimal
  Statistics:
    Branch and bound:
      Number of bounded subproblems: 0
      Number of created subproblems: 0
  Error rc: 0
  Time: 0.0022733211517333984
# ----------------------------------------------------------
#   Solution Information
# ----------------------------------------------------------
Solution:
- number of solutions: 0
  number of solutions displayed: 0

/home/docs/checkouts/readthedocs.org/user_builds/pypsa/conda/v0.19.1/lib/python3.10/site-packages/pypsa/opf.py:1293: FutureWarning: Using the level keyword in DataFrame and Series aggregations is deprecated and will be removed in a future version. Use groupby instead. df.sum(level=1) should use df.groupby(level=1).sum().
  pd.concat({c.name:

[11]:

	Voltage Angles	Volate Magnitude
Bus
MV bus	0.000000	1.0
LV1 bus	-0.793104	1.0
LV2 bus	-1.090326	1.0