Revise export ports data

Snakefile

@@ -1003,6 +1003,7 @@ rule solve_sector_networks:
 rule prepare_ports:
     output:
         ports="data/ports.csv",  # TODO move from data to resources
+        export_ports="resources/" + SECDIR + "export_ports.csv",
     script:
         "scripts/prepare_ports.py"
 
@@ -1154,9 +1155,11 @@ rule add_export:
         export_profile=config["export"]["export_profile"],
         snapshots=config["snapshots"],
         costs=config["costs"],
+        custom_export=config["custom_data"]["export_data"],
     input:
         overrides="data/override_component_attrs",
-        export_ports="data/export_ports.csv",
+        custom_export_ports="data/custom/export_ports.csv",
+        export_ports="resources/" + SECDIR + "export_ports.csv",
         costs=COSTDIR + "costs_{planning_horizons}.csv",
         ship_profile="resources/" + SECDIR + "ship_profile_{h2export}TWh.csv",
         network=RESDIR

config.default.yaml

@@ -478,6 +478,7 @@ custom_data:
   add_existing: false
   custom_sectors: false
   gas_network: false # If "True" then a custom .csv file must be placed in "resources/custom_data/pipelines.csv" , If "False" the user can choose btw "greenfield" or Model built-in datasets. Please refer to ["sector"] below.
+  export_data: false # If "True" then a custom .csv file must be placed in "data/custom/export_ports.csv"
 
 industry:
   reference_year: 2015

doc/release_notes.rst

@@ -48,6 +48,8 @@ E.g. if a new rule becomes available describe how to use it `make test` and in o
 
 * Drop entries that contain non-string elements in country column of `CO2_emissions_csv` data in `prepare_transport_data_input.py` script `PR #1166 <https://github.com/pypsa-meets-earth/pypsa-earth/pull/1166>`_
 
+* Revise ports data for export in `add_export.py` related to sector model `PR #1175 <https://github.com/pypsa-meets-earth/pypsa-earth/pull/1175>`_
+
 PyPSA-Earth 0.4.1
 =================
 

scripts/add_export.py

@@ -33,12 +33,20 @@ def select_ports(n):
     This function selects the buses where ports are located.
     """
 
+    if snakemake.params.custom_export:
+        input_port_data = snakemake.input.custom_export_ports
+    else:
+        input_port_data = snakemake.input.export_ports
+
     ports = pd.read_csv(
-        snakemake.input.export_ports,
+        input_port_data,
         index_col=None,
         keep_default_na=False,
     ).squeeze()
 
+    # ports = raw_ports[["name", "country", "fraction", "x", "y"]]
+    # ports.loc[:, "fraction"] = ports.fraction.round(1)
+
     ports = ports[ports.country.isin(countries)]
     if len(ports) < 1:
         logger.error(

scripts/prepare_ports.py

@@ -31,6 +31,36 @@ def download_ports():
     return wpi_csv
 
 
+def filter_ports(dataframe):
+    """
+    Filters ports based on their harbor size and returns a DataFrame containing
+    only the largest port for each country.
+    """
+    # Filter large sized ports
+    large_ports = dataframe[dataframe["Harbor Size"] == "Large"]
+    countries_with_large_ports = large_ports["country"].unique()
+
+    # Filter out countries with large ports
+    remaining_ports = dataframe[~dataframe["country"].isin(countries_with_large_ports)]
+
+    # Filter medium sized ports from remaining ports
+    medium_ports = remaining_ports[remaining_ports["Harbor Size"] == "Medium"]
+    countries_with_medium_ports = medium_ports["country"].unique()
+
+    # Filter out countries with medium ports
+    remaining_ports = remaining_ports[
+        ~remaining_ports["country"].isin(countries_with_medium_ports)
+    ]
+
+    # Filter small sized ports from remaining ports
+    small_ports = remaining_ports[remaining_ports["Harbor Size"] == "Small"]
+
+    # Combine all filtered ports
+    filtered_ports = pd.concat([large_ports, medium_ports, small_ports])
+
+    return filtered_ports
+
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
@@ -102,3 +132,6 @@ def download_ports():
     ports["fraction"] = ports["Harbor_size_nr"] / ports["Total_Harbor_size_nr"]
 
     ports.to_csv(snakemake.output[0], sep=",", encoding="utf-8", header="true")
+    filter_ports(ports).to_csv(
+        snakemake.output[1], sep=",", encoding="utf-8", header="true"
+    )

test/config.test_myopic.yaml

@@ -91,6 +91,7 @@ custom_data:
   add_existing: false
   custom_sectors: false
   gas_network: false # If "True" then a custom .csv file must be placed in "resources/custom_data/pipelines.csv" , If "False" the user can choose btw "greenfield" or Model built-in datasets. Please refer to ["sector"] below.
+  export_data: false # If "True" then a custom .csv file must be placed in "data/custom/export.csv"
 
 
 costs: # Costs used in PyPSA-Earth-Sec. Year depends on the wildcard planning_horizon in the scenario section