Merge pull request #390 from calliope-project/feature-hot-water

Separate hot water and space heating demand profiles

CHANGELOG.md

@@ -8,7 +8,7 @@
 
 * **ADD** Spatial resolution that aligns with the regions defined by the [e-Highway 2050 project](https://cordis.europa.eu/project/id/308908/reporting) (`ehighways`) (#370).
 
-* **ADD** fully-electrified heat demand (#284).
+* **ADD** fully-electrified heat demand (#284, #343, #390, #391).
 
 * **ADD** fully-electrified road transportation (#270, #271, #358). A parameter allows to define the share of uncontrolled (timeseries) vs controlled charging (optimised) by the solver (#338). Data for controlled charging constraints is readily available (#356), but corresponding constraints are not yet implemented (#385).
 

config/default.yaml

@@ -21,8 +21,7 @@ data-sources:
     swiss-industry-energy-balance: https://www.bfe.admin.ch/bfe/en/home/versorgung/statistik-und-geodaten/energiestatistiken/teilstatistiken.exturl.html/aHR0cHM6Ly9wdWJkYi5iZmUuYWRtaW4uY2gvZGUvcHVibGljYX/Rpb24vZG93bmxvYWQvODc4OA==.html
     controlled-ev-profiles: https://zenodo.org/record/6579421/files/ramp-ev-{dataset}.csv.gz?download=1
     uncontrolled-ev-profiles: https://sandbox.zenodo.org/records/45530/files/uncontrolled-charging-profiles.csv.gz?download=1 # TODO: convert into Zenodo repository
-    gridded-temperature-data: https://zenodo.org/records/6557643/files/temperature.nc?download=1
-    gridded-10m-windspeed-data: https://zenodo.org/records/6557643/files/wind10m.nc?download=1
+    gridded-weather-data: https://zenodo.org/records/11516744/files/{data_var}.nc
     when2heat-params: https://zenodo.org/records/10965295/files/{dataset}?download=1
     population: https://ec.europa.eu/eurostat/cache/GISCO/geodatafiles/JRC_GRID_2018.zip
 data-pre-processing:

config/schema.yaml

@@ -111,14 +111,10 @@ properties:
                 type: string
                 pattern: ^(https?|http?):\/\/.+
                 description: Web address of electric light-duty vehicle uncontrolled charging.
-            gridded-temperature-data:
+            gridded-weather-data:
                 type: string
-                pattern: ^(https?|http?):\/\/.+
-                description: "Web address of gridded temperature data. Expecting a netCDF file with the coordinates [time, site], and the variables [temperature, lat, lon]."
-            gridded-10m-windspeed-data:
-                type: string
-                pattern: ^(https?|http?):\/\/.+
-                description: "Web address of gridded 10m wind speed data. Expecting a netCDF file with the coordinates [time, site], and the variables [temperature, lat, lon]."
+                pattern: ^(https?|http?):\/\/.+{data_var}.*\.(nc)$
+                description: "Web address of gridded weather data. Expecting a netCDF file with the coordinates [time, site], the variables [{data_var}, lat, lon], and the attribute 'unit'."
             when2heat-params:
                 type: string
                 pattern: ^(https?|http?):\/\/.+

rules/heat.smk

@@ -1,16 +1,7 @@
-rule download_gridded_temperature_data:
-    message: "Download gridded temperature data"
-    params: url = config["data-sources"]["gridded-temperature-data"]
-    output: protected("data/automatic/gridded-weather/temperature.nc")
-    conda: "../envs/shell.yaml"
-    localrule: True
-    shell: "curl -sSLo {output} '{params.url}'"
-
-
-rule download_gridded_10m_windspeed_data:
-    message: "Download gridded 10m wind speed data"
-    params: url = config["data-sources"]["gridded-10m-windspeed-data"]
-    output: protected("data/automatic/gridded-weather/wind10m.nc")
+rule download_gridded_weather_data:
+    message: "Download gridded {wildcards.data_var} data"
+    params: url = lambda wildcards: config["data-sources"]["gridded-weather-data"].format(data_var=wildcards.data_var)
+    output: protected("data/automatic/gridded-weather/{data_var}.nc")
     conda: "../envs/shell.yaml"
     localrule: True
     shell: "curl -sSLo {output} '{params.url}'"
@@ -87,10 +78,11 @@ use rule create_heat_demand_timeseries as create_heat_demand_timeseries_historic
     output:
         "build/models/{resolution}/timeseries/demand/heat-demand-historic-electrification.csv",
 
+
 rule population_per_weather_gridbox:
     message: "Get {wildcards.resolution} population information per weather data gridbox"
     input:
-        wind_speed = rules.download_gridded_10m_windspeed_data.output[0],
+        weather_grid = "data/automatic/gridded-weather/grid.nc",
         population = rules.raw_population_unzipped.output[0],
         locations = rules.units.output[0]
     params:
@@ -103,14 +95,15 @@ rule population_per_weather_gridbox:
 
 rule unscaled_heat_profiles:
     message: "Generate gridded heat demand profile shapes for {wildcards.year} from weather and population data"
+
     input:
         population = rules.population_per_weather_gridbox.output[0],
-        wind_speed = rules.download_gridded_10m_windspeed_data.output[0],
-        temperature = rules.download_gridded_temperature_data.output[0],
+        wind_speed = "data/automatic/gridded-weather/wind10m.nc",
+        temperature = "data/automatic/gridded-weather/temperature.nc",
         when2heat = rules.download_when2heat_params.output[0]
     params:
-        lat_name = "lat",
-        lon_name = "lon",
+        first_year = config["scope"]["temporal"]["first-year"],
+        final_year = config["scope"]["temporal"]["final-year"],
     conda: "../envs/default.yaml"
-    output: "build/data/{resolution}/gridded_hourly_unscaled_heat_demand_{year}.nc"
+    output: "build/data/{resolution}/hourly_unscaled_heat_demand.nc"
     script: "../scripts/heat/unscaled_heat_profiles.py"

scripts/heat/population_per_gridbox.py

@@ -96,7 +96,7 @@ def population_on_weather_grid(
     population_on_weather_grid(
         path_to_population=snakemake.input.population,
         path_to_locations=snakemake.input.locations,
-        path_to_coordinates=snakemake.input.wind_speed,
+        path_to_coordinates=snakemake.input.weather_grid,
         lat_name=snakemake.params.lat_name,
         lon_name=snakemake.params.lon_name,
         out_path=snakemake.output[0],