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base_network: Fix bug in _closest_links and fix SACOI capacity

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This commit is contained in:
Jonas Hörsch 2018-09-27 18:27:33 +02:00
parent 72b484dd6b
commit 37d817c70f
2 changed files with 10 additions and 3 deletions
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1
data/parameter_corrections.yaml
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@ -17,6 +17,7 @@ Link:
"8106": 1000 # ALEGrO BE-DE "8106": 1000 # ALEGrO BE-DE
"5241": 1000 # NEMO GB-BE "5241": 1000 # NEMO GB-BE
"7719": 700 # Cobra DK-NL "7719": 700 # Cobra DK-NL
"5362": 300 # SACOI (between Sardignia and Corse)
index: index:
"11384": 1000 # NO-DK (part 1) "11384": 1000 # NO-DK (part 1)
"11087": 1000 # NO-DK (part 2) "11087": 1000 # NO-DK (part 2)

12
scripts/base_network.py
View File

@ -19,6 +19,9 @@ logger = logging.getLogger(__name__)
import pypsa import pypsa
def _get_oid(df):
return df.tags.str.extract('"oid"=>"(\d+)"', expand=False)
def _find_closest_links(links, new_links, distance_upper_bound=1.5): def _find_closest_links(links, new_links, distance_upper_bound=1.5):
tree = sp.spatial.KDTree(np.vstack([ tree = sp.spatial.KDTree(np.vstack([
new_links[['x1', 'y1', 'x2', 'y2']], new_links[['x1', 'y1', 'x2', 'y2']],
@ -31,8 +34,11 @@ def _find_closest_links(links, new_links, distance_upper_bound=1.5):
distance_upper_bound=distance_upper_bound distance_upper_bound=distance_upper_bound
) )
found_b = ind < 2 * len(new_links)
return ( return (
pd.DataFrame(dict(D=dist, i=new_links.index[ind % len(new_links)]), index=links.index) pd.DataFrame(dict(D=dist[found_b],
i=new_links.index[ind[found_b] % len(new_links)]),
index=links.index[found_b])
.groupby('i').D.idxmin() .groupby('i').D.idxmin()
) )
@ -157,13 +163,13 @@ def _apply_parameter_corrections(n):
if corrections is None: return if corrections is None: return
for component, attrs in iteritems(corrections): for component, attrs in iteritems(corrections):
df = n.df(component) df = n.df(component)
oid = _get_oid(df)
if attrs is None: continue if attrs is None: continue
for attr, repls in iteritems(attrs): for attr, repls in iteritems(attrs):
for i, r in iteritems(repls): for i, r in iteritems(repls):
if i == 'oid': if i == 'oid':
df["oid"] = df.tags.str.extract('"oid"=>"(\d+)"', expand=False) r = oid.map(repls["oid"]).dropna()
r = df.oid.map(repls["oid"]).dropna()
elif i == 'index': elif i == 'index':
r = pd.Series(repls["index"]) r = pd.Series(repls["index"])
else: else: