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pf: Refactor line and transformer_types
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Raise an error, if any types are missing.
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@coroa
coroa committed Dec 17, 2017
1 parent 747e0db commit 783dbb4
Showing 1 changed file with 32 additions and 43 deletions.
75 changes: 32 additions & 43 deletions pypsa/pf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -414,28 +414,25 @@ def apply_line_types(network):
"""

lines_with_types_b = network.lines.type != ""

if lines_with_types_b.zsum() == 0:
return

for attr in ["r","x"]:
attr_per_length = network.line_types[attr + "_per_length"]
network.lines.loc[lines_with_types_b,attr] = (
network.lines.loc[lines_with_types_b, "type"].map(attr_per_length)
* network.lines.loc[lines_with_types_b, "length"]
/ network.lines.loc[lines_with_types_b, "num_parallel"]
)
missing_types = (pd.Index(network.lines.loc[lines_with_types_b, 'type'].unique())
.difference(network.line_types.index))
assert missing_types.empty, ("The type(s) {} do(es) not exist in network.line_types"
.format(", ".join(missing_types)))

factor = 2*np.pi*1e-9*network.lines.loc[lines_with_types_b, "type"].map(network.line_types.f_nom)
c_per_length = network.line_types["c_per_length"]
network.lines.loc[lines_with_types_b, "b"] = (
factor
* network.lines.loc[lines_with_types_b, "type"].map(c_per_length)
* network.lines.loc[lines_with_types_b, "length"]
* network.lines.loc[lines_with_types_b, "num_parallel"]
)
# Get a copy of the lines data
l = (network.lines.loc[lines_with_types_b, ["type", "length", "num_parallel"]]
.join(network.line_types, on='type'))

for attr in ["r","x"]:
l[attr] = l[attr + "_per_length"] * l["length"] / l["num_parallel"]
l["b"] = 2*np.pi*1e-9*l["f_nom"] * l["c_per_length"] * l["length"] * l["num_parallel"]

# now set calculated values on live lines
for attr in ["r", "x", "b"]:
network.lines.loc[lines_with_types_b, attr] = l[attr]



Expand All @@ -445,50 +442,42 @@ def apply_transformer_types(network):
"""

trafos = network.transformers
trafos_with_types_b = trafos.type != ""

trafos_with_types_b = network.transformers.type != ""
if trafos_with_types_b.zsum() == 0:
return

trafos.loc[trafos_with_types_b, "r"] = trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["vscr"])/100.

z = trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["vsc"])/100.
missing_types = (pd.Index(network.transformers.loc[trafos_with_types_b, 'type'].unique())
.difference(network.transformer_types.index))
assert missing_types.empty, ("The type(s) {} do(es) not exist in network.transformer_types"
.format(", ".join(missing_types)))

trafos.loc[trafos_with_types_b, "x"] = np.sqrt(z**2 - trafos.loc[trafos_with_types_b, "r"]**2)
# Get a copy of the transformers data
# (joining pulls in "phase_shift", "s_nom", "tap_side" from TransformerType)
t = (network.transformers.loc[trafos_with_types_b, ["type", "tap_position", "num_parallel"]]
.join(network.transformer_types, on='type'))

for attr in ["phase_shift","s_nom"]:
trafos.loc[trafos_with_types_b, attr] = trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types[attr])
t["r"] = t["vscr"] /100.
t["x"] = np.sqrt((t["vsc"]/100.)**2 - t["r"]**2)

#NB: b and g are per unit of s_nom
trafos.loc[trafos_with_types_b, "g"] = trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["pfe"])/(1000. * trafos.loc[trafos_with_types_b, "s_nom"])

i0 = trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["i0"])/100.

b_minus_squared = i0**2 - trafos.loc[trafos_with_types_b, "g"]**2
t["g"] = t["pfe"]/(1000. * t["s_nom"])

#for some bizarre reason, some of the standard types in pandapower have i0^2 < g^2

b_minus_squared[b_minus_squared < 0.] = 0.

trafos.loc[trafos_with_types_b, "b"] = - np.sqrt(b_minus_squared)

t["b"] = - np.sqrt(((t["i0"]/100.)**2 - t["g"]**2).clip(lower=0))

for attr in ["r","x"]:
trafos.loc[trafos_with_types_b, attr] = trafos.loc[trafos_with_types_b, attr]/trafos.loc[trafos_with_types_b, "num_parallel"]
t[attr] /= t["num_parallel"]

for attr in ["b","g"]:
trafos.loc[trafos_with_types_b, attr] = trafos.loc[trafos_with_types_b, attr]*trafos.loc[trafos_with_types_b, "num_parallel"]

t[attr] *= t["num_parallel"]

#deal with tap positions

trafos.loc[trafos_with_types_b, "tap_ratio"] = 1 + (
trafos.loc[trafos_with_types_b, "tap_position"] -
trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["tap_neutral"])) * (
trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["tap_step"])/100.)
t["tap_ratio"] = 1. + (t["tap_position"] - t["tap_neutral"]) * (t["tap_step"]/100.)

trafos.loc[trafos_with_types_b, "tap_side"] = trafos.loc[trafos_with_types_b, "type"].map(network.transformer_types["tap_side"])
# now set calculated values on live transformers
for attr in ["r", "x", "g", "b", "phase_shift", "s_nom", "tap_side", "tap_ratio"]:
network.transformers.loc[trafos_with_types_b, attr] = t[attr]

#TODO: status, rate_A

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