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Merge pull request #676 from openego/fixes/#660-fix-ehv-clustering
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Fixes/#660 fix ehv clustering
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@ClaraBuettner
ClaraBuettner authored Oct 26, 2023
2 parents 90eae0d + 79ecf3e commit 944c5cc
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25 changes: 23 additions & 2 deletions etrago/appl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -102,7 +102,11 @@
"generator_noise": 789456, # apply generator noise, False or seed number
"extra_functionality": {}, # Choose function name or {}
# Spatial Complexity:
"network_clustering_ehv": False, # clustering of HV buses to EHV buses
"delete_dispensable_ac_buses": True, # bool. Find and delete expendable buses
"network_clustering_ehv": {
"active": False, # choose if clustering of HV buses to EHV buses is activated
"busmap": False, # False or path to stored busmap
},
"network_clustering": {
"active": True, # choose if clustering is activated
"method": "kmedoids-dijkstra", # choose clustering method: kmeans or kmedoids-dijkstra
Expand Down Expand Up @@ -383,11 +387,28 @@ def run_etrago(args, json_path):
Limit overall energy production country-wise for each generator
by carrier. Set upper/lower limit in p.u.
network_clustering_ehv : bool
delete_dispensable_ac_buses: bool
Choose if electrical buses that are only connecting two lines should be
removed. These buses have no other components attached to them. The
connected lines are merged. This reduces the spatial complexity without
losing any accuracy.
Default: True.
network_clustering_ehv : dict
Choose if you want to apply an extra high voltage clustering to the
electrical network.
The provided dictionary can have the following entries:
* "active" : bool
Choose if you want to cluster the full HV/EHV dataset down to only the
EHV buses. In that case, all HV buses are assigned to their closest EHV
substation, taking into account the shortest distance on power lines.
Default: False.
* "busmap" : str
Choose if an stored busmap can be used to make the process quicker, or
a new busmap must be calculated. False or path to the busmap in csv
format should be given.
Default: False
network_clustering : dict
Choose if you want to apply a clustering of all network buses and
specify settings.
Expand Down
6 changes: 5 additions & 1 deletion etrago/args.json
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,11 @@
},
"generator_noise": 789456,
"extra_functionality": {},
"network_clustering_ehv": false,
"delete_dispensable_ac_buses": true,
"network_clustering_ehv": {
"active": false,
"busmap": false,
},
"network_clustering": {
"active": true,
"method": "kmedoids-dijkstra",
Expand Down
146 changes: 60 additions & 86 deletions etrago/cluster/electrical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@
import pypsa.io as io

from etrago.cluster.spatial import (
busmap_from_psql,
busmap_ehv_clustering,
group_links,
kmean_clustering,
kmedoids_dijkstra_clustering,
Expand Down Expand Up @@ -115,6 +115,27 @@ def adjust_no_electric_network(etrago, busmap, cluster_met):
Maps old bus_ids to new bus_ids including all sectors.
"""

def find_de_closest(network, bus_ne):
ac_ehv = network.buses[
(network.buses.v_nom > 110)
& (network.buses.carrier == "AC")
& (network.buses.country == "DE")
]

bus_ne_x = network.buses.loc[bus_ne, "x"]
bus_ne_y = network.buses.loc[bus_ne, "y"]

ac_ehv["dist"] = ac_ehv.apply(
lambda x: ((x.x - bus_ne_x) ** 2 + (x.y - bus_ne_y) ** 2)
** (1 / 2),
axis=1,
)

new_ehv_bus = ac_ehv.dist.idxmin()

return new_ehv_bus

network = etrago.network
# network2 is supposed to contain all the not electrical or gas buses
# and links
Expand All @@ -135,16 +156,9 @@ def adjust_no_electric_network(etrago, busmap, cluster_met):
"rural_heat": "rural_heat_pump",
}

# no_elec_to_cluster maps the no electrical buses to the eHV/kmean bus
no_elec_to_cluster = pd.DataFrame(
columns=["cluster", "carrier", "new_bus"]
).set_index("new_bus")

max_bus = max([int(item) for item in network.buses.index.to_list()])

no_elec_conex = []
# busmap2 maps all the no electrical buses to the new buses based on the
# eHV network
# busmap2 defines how the no electrical buses directly connected to AC
# are going to be clustered
busmap2 = {}

# Map crossborder AC buses in case that they were not part of the k-mean
Expand All @@ -160,53 +174,37 @@ def adjust_no_electric_network(etrago, busmap, cluster_met):
for bus_out in ac_buses_out.index:
busmap2[bus_out] = bus_out

foreign_hv = network.buses[
(network.buses.country != "DE")
& (network.buses.carrier == "AC")
& (network.buses.v_nom > 110)
].index
busmap3 = pd.DataFrame(columns=["elec_bus", "carrier", "cluster"])
for bus_ne in network2.buses.index:
bus_hv = -1
carry = network2.buses.loc[bus_ne, "carrier"]

if (
len(
network2.links[
(network2.links["bus1"] == bus_ne)
& (network2.links["carrier"] == map_carrier[carry])
]
)
> 0
):
busmap3.at[bus_ne, "carrier"] = carry
try:
df = network2.links[
(network2.links["bus1"] == bus_ne)
& (network2.links["carrier"] == map_carrier[carry])
].copy()
df["elec"] = df["bus0"].isin(busmap.keys())

df = df[df["elec"]]
if len(df) > 0:
bus_hv = df["bus0"][0]

if bus_hv == -1:
busmap2[bus_ne] = str(bus_ne)
bus_hv = df[df["elec"]]["bus0"][0]
bus_ehv = busmap[bus_hv]
if bus_ehv not in foreign_hv:
busmap3.at[bus_ne, "elec_bus"] = bus_ehv
else:
busmap3.at[bus_ne, "elec_bus"] = find_de_closest(
network, bus_ne
)
except:
no_elec_conex.append(bus_ne)
continue

if (
(no_elec_to_cluster.cluster == busmap[bus_hv])
& (no_elec_to_cluster.carrier == carry)
).any():
bus_cluster = no_elec_to_cluster[
(no_elec_to_cluster.cluster == busmap[bus_hv])
& (no_elec_to_cluster.carrier == carry)
].index[0]
else:
bus_cluster = str(max_bus + 1)
max_bus = max_bus + 1
new = pd.DataFrame(
{"cluster": busmap[bus_hv], "carrier": carry},
index=[bus_cluster],
)
busmap3.at[bus_ne, "elec_bus"] = bus_ne

no_elec_to_cluster = pd.concat([no_elec_to_cluster, new])
for a, df in busmap3.groupby(["elec_bus", "carrier"]):
busmap3.loc[df.index, "cluster"] = df.index[0]

busmap2[bus_ne] = bus_cluster
busmap3 = busmap3["cluster"].to_dict()

if no_elec_conex:
logger.info(
Expand All @@ -215,17 +213,17 @@ def adjust_no_electric_network(etrago, busmap, cluster_met):
)

# rural_heat_store buses are clustered based on the AC buses connected to
# their corresponding rural_heat buses
# their corresponding rural_heat buses. Results saved in busmap4
links_rural_store = etrago.network.links[
etrago.network.links.carrier == "rural_heat_store_charger"
].copy()

busmap3 = {}
links_rural_store["to_ac"] = links_rural_store["bus0"].map(busmap2)
busmap4 = {}
links_rural_store["to_ac"] = links_rural_store["bus0"].map(busmap3)
for rural_heat_bus, df in links_rural_store.groupby("to_ac"):
cluster_bus = df.bus1.iat[0]
for rural_store_bus in df.bus1:
busmap3[rural_store_bus] = cluster_bus
busmap4[rural_store_bus] = cluster_bus

# Add the gas buses to the busmap and map them to themself
for gas_bus in network.buses[
Expand All @@ -236,28 +234,8 @@ def adjust_no_electric_network(etrago, busmap, cluster_met):
].index:
busmap2[gas_bus] = gas_bus

busmap = {**busmap, **busmap2, **busmap3}
busmap = {**busmap, **busmap2, **busmap3, **busmap4}

# The new buses based on the eHV network for not electrical buses are
# created
if cluster_met in ["kmeans", "kmedoids-dijkstra"]:
network.madd(
"Bus",
names=no_elec_to_cluster.index,
carrier=no_elec_to_cluster.carrier,
)

else:
network.madd(
"Bus",
names=no_elec_to_cluster.index,
carrier=no_elec_to_cluster.carrier.values,
x=network.buses.loc[no_elec_to_cluster.cluster.values, "x"].values,
y=network.buses.loc[no_elec_to_cluster.cluster.values, "y"].values,
country=network.buses.loc[
no_elec_to_cluster.cluster.values, "country"
].values,
)
return network, busmap


Expand Down Expand Up @@ -290,11 +268,6 @@ def cluster_on_extra_high_voltage(etrago, busmap, with_time=True):
etrago, busmap, cluster_met="ehv"
)

pd.DataFrame(busmap.items(), columns=["bus0", "bus1"]).to_csv(
"ehv_elecgrid_busmap_result.csv",
index=False,
)

buses = aggregatebuses(
network,
busmap,
Expand All @@ -321,6 +294,8 @@ def cluster_on_extra_high_voltage(etrago, busmap, with_time=True):
# Dealing with links
links = network.links.copy()
dc_links = links[links["carrier"] == "DC"]
# Discard links connected to buses under 220 kV
dc_links = dc_links[dc_links.bus0.isin(buses.index)]
links = links[links["carrier"] != "DC"]

new_links = (
Expand Down Expand Up @@ -379,7 +354,6 @@ def cluster_on_extra_high_voltage(etrago, busmap, with_time=True):
io.import_series_from_dataframe(network_c, df, one_port, attr)

network_c.links, network_c.links_t = group_links(network_c)

network_c.determine_network_topology()

return (network_c, busmap)
Expand Down Expand Up @@ -412,10 +386,10 @@ def delete_ehv_buses_no_lines(network):
buses_ac["with_gen"] = buses_ac.index.isin(network.generators.bus)

delete_buses = buses_ac[
(buses_ac["with_line"] is False)
& (buses_ac["with_load"] is False)
& (buses_ac["with_link"] is False)
& (buses_ac["with_gen"] is False)
(~buses_ac["with_line"])
& (~buses_ac["with_load"])
& (~buses_ac["with_link"])
& (~buses_ac["with_gen"])
].index

if len(delete_buses):
Expand Down Expand Up @@ -453,8 +427,8 @@ def ehv_clustering(self):
"""
Cluster the network based on Extra High Voltage (EHV) grid.
If `network_clustering_ehv` argument is True, the function clusters the
network based on the EHV grid.
If 'active' in the `network_clustering_ehv` argument is True, the function
clusters the network based on the EHV grid.
Parameters
----------
Expand All @@ -466,14 +440,14 @@ def ehv_clustering(self):
None
"""

if self.args["network_clustering_ehv"]:
if self.args["network_clustering_ehv"]["active"]:
logger.info("Start ehv clustering")

self.network.generators.control = "PV"

delete_ehv_buses_no_lines(self.network)

busmap = busmap_from_psql(self)
busmap = busmap_ehv_clustering(self)

self.network, busmap = cluster_on_extra_high_voltage(
self, busmap, with_time=True
Expand Down
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