add release notes, minor code improvements

doc/release_notes.rst

@@ -28,6 +28,24 @@ Upcoming Release
 
 * Cluster residential and services heat buses by default. Can be disabled with ``cluster_heat_buses: false``.
 
+* Bugfix: Do not reduce district heat share when building population-weighted
+  energy statistics. Previously the district heating share was being multiplied
+  by the population weighting, reducing the DH share with multiple nodes.
+
+* Move building of daily heat profile to its own rule
+  :mod:`build_hourly_heat_demand` from :mod:`prepare_sector_network`.
+
+* In :mod:`build_energy_totals`, district heating shares are now reported in a
+  separate file.
+
+* Move calculation of district heating share to its own rule
+  :mod:`build_district_heat_share`.
+
+* Move building of distribution of existing heating to own rule
+  :mod:`build_existing_heating_distribution`. This makes the distribution of
+  existing heating to urban/rural, residential/services and spatially more
+  transparent.
+
 
 PyPSA-Eur 0.9.0 (5th January 2024)
 ==================================

doc/sector.rst

@@ -20,6 +20,12 @@ Rule ``add_existing_baseyear``
 
 .. automodule:: add_existing_baseyear
 
+Rule ``build_existing_heating_distribution``
+==============================================================================
+
+.. automodule:: build_existing_heating_distribution
+
+
 Rule ``build_ammonia_production``
 ==============================================================================
 
@@ -60,10 +66,20 @@ Rule ``build_gas_network``
 
 .. automodule:: build_gas_network
 
-Rule ``build_heat_demand``
+Rule ``build_daily_heat_demand``
 ==============================================================================
 
-.. automodule:: build_heat_demand
+.. automodule:: build_daily_heat_demand
+
+Rule ``build_hourly_heat_demand``
+==============================================================================
+
+.. automodule:: build_hourly_heat_demand
+
+Rule ``build_district_heat_share``
+==============================================================================
+
+.. automodule:: build_district_heat_share
 
 Rule ``build_industrial_distribution_key``
 ==============================================================================

rules/solve_overnight.smk

@@ -28,9 +28,10 @@ rule solve_sector_network:
         + "logs/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log",
         python=RESULTS
         + "logs/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log",
-    threads: config["solving"]["solver_options"][config["solving"]["solver"]["options"]].get(
+    threads:
-    "threads", 4
+        config["solving"]["solver_options"][
-)
+            config["solving"]["solver"]["options"]
+        ].get("threads", 4)
     resources:
         mem_mb=config["solving"]["mem"],
         walltime=config["solving"].get("walltime", "12:00:00"),

scripts/add_existing_baseyear.py

@@ -451,7 +451,7 @@ def add_heating_capacities_installed_before_baseyear(
                 efficiency=efficiency,
                 capital_cost=costs.at[costs_name, "efficiency"]
                 * costs.at[costs_name, "fixed"],
-                p_nom=existing_heating[(name, f"{heat_pump_type} heat pump")][nodes] * ratio / costs.at[costs_name, "efficiency"],
+                p_nom=existing_heating.loc[nodes, (name, f"{heat_pump_type} heat pump")] * ratio / costs.at[costs_name, "efficiency"],
                 build_year=int(grouping_year),
                 lifetime=costs.at[costs_name, "lifetime"],
             )
@@ -470,7 +470,7 @@ def add_heating_capacities_installed_before_baseyear(
                     * costs.at[f"{name_type} resistive heater", "fixed"]
                 ),
                 p_nom=(
-                    existing_heating[(name, "resistive heater")][nodes]
+                    existing_heating.loc[nodes, (name, "resistive heater")]
                     * ratio
                     / costs.at[f"{name_type} resistive heater", "efficiency"]
                 ),
@@ -493,7 +493,7 @@ def add_heating_capacities_installed_before_baseyear(
                     * costs.at[f"{name_type} gas boiler", "fixed"]
                 ),
                 p_nom=(
-                    existing_heating[(name, "gas boiler")][nodes]
+                    existing_heating.loc[nodes, (name, "gas boiler")]
                     * ratio
                     / costs.at[f"{name_type} gas boiler", "efficiency"]
                 ),
@@ -514,7 +514,7 @@ def add_heating_capacities_installed_before_baseyear(
                 capital_cost=costs.at["decentral oil boiler", "efficiency"]
                 * costs.at["decentral oil boiler", "fixed"],
                 p_nom= (
-                    existing_heating[(name, "oil boiler")][nodes]
+                    existing_heating.loc[nodes, (name, "oil boiler")]
                     * ratio
                     / costs.at["decentral oil boiler", "efficiency"]),
                 build_year=int(grouping_year),

scripts/build_daily_heat_demand.py

@@ -18,7 +18,8 @@ if __name__ == "__main__":
         from _helpers import mock_snakemake
 
         snakemake = mock_snakemake(
-            "build_heat_demands",
+            "build_daily_heat_demands",
+            scope="total",
             simpl="",
             clusters=48,
         )

scripts/build_district_heat_share.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors
+# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
 #
 # SPDX-License-Identifier: MIT
 """
@@ -21,9 +21,10 @@ if __name__ == "__main__":
         from _helpers import mock_snakemake
 
         snakemake = mock_snakemake(
-            "build_heat_demands",
+            "build_district_heat_share",
             simpl="",
             clusters=48,
+            planning_horizons="2050",
         )
 
     investment_year = int(snakemake.wildcards.planning_horizons[-4:])
@@ -68,10 +69,10 @@ if __name__ == "__main__":
         f"resulting in new average share of {dist_fraction_node.mean():.2%}"
     )
 
-    df = pd.DataFrame(dtype=float)
+    df = pd.DataFrame({
-
+        "original district heat share": district_heat_share,
-    df["original district heat share"] = district_heat_share
+        "district fraction of node": dist_fraction_node,
-    df["district fraction of node"] = dist_fraction_node
+        "urban fraction": urban_fraction
-    df["urban fraction"] = urban_fraction
+    }, dtype=float)
 
     df.to_csv(snakemake.output.district_heat_share)

scripts/build_energy_totals.py

@@ -583,10 +583,10 @@ def build_district_heat_share(countries, idees):
     # Missing district heating share
     dh_share = pd.read_csv(
         snakemake.input.district_heat_share, index_col=0, usecols=[0, 1]
-    )
+    ).div(100).squeeze()
     # make conservative assumption and take minimum from both data sets
     district_heat_share = pd.concat(
-        [district_heat_share, dh_share.reindex(index=district_heat_share.index) / 100], axis=1
+        [district_heat_share, dh_share.reindex_like(district_heat_share)], axis=1
     ).min(axis=1)
 
     district_heat_share.name = "district heat share"

scripts/build_existing_heating_distribution.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-# SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors
+# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
 #
 # SPDX-License-Identifier: MIT
 """
@@ -7,8 +7,6 @@ Builds table of existing heat generation capacities for initial planning
 horizon.
 """
 import pandas as pd
-import sys
-from pypsa.descriptors import Dict
 import numpy as np
 import country_converter as coco
 
@@ -17,19 +15,13 @@ cc = coco.CountryConverter()
 
 def build_existing_heating():
     # retrieve existing heating capacities
-    techs = [
-        "gas boiler",
-        "oil boiler",
-        "resistive heater",
-        "air heat pump",
-        "ground heat pump",
-    ]
 
     existing_heating = pd.read_csv(snakemake.input.existing_heating,
                                    index_col=0,
                                    header=0)
 
-    # data for Albania, Montenegro and Macedonia not included in database                                                                          existing_heating.loc["Albania"] = np.nan
+    # data for Albania, Montenegro and Macedonia not included in database
+    existing_heating.loc["Albania"] = np.nan
     existing_heating.loc["Montenegro"] = np.nan
     existing_heating.loc["Macedonia"] = np.nan
 
@@ -104,5 +96,14 @@ def build_existing_heating():
 
 
 if __name__ == "__main__":
+    if "snakemake" not in globals():
+        from _helpers import mock_snakemake
+
+        snakemake = mock_snakemake(
+            "build_existing_heating_distribution",
+            simpl="",
+            clusters=48,
+            planning_horizons=2050,
+        )
 
     build_existing_heating()

scripts/build_hourly_heat_demand.py

@@ -6,19 +6,19 @@
 Build hourly heat demand time series from daily ones.
 """
 
-import pandas as pd
-import xarray as xr
-from _helpers import generate_periodic_profiles, update_config_with_sector_opts
 from itertools import product
 
-
+import pandas as pd
+import xarray as xr
+from _helpers import generate_periodic_profiles
 
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
 
         snakemake = mock_snakemake(
-            "build_heat_demands",
+            "build_hourly_heat_demands",
+            scope="total",
             simpl="",
             clusters=48,
         )
@@ -58,12 +58,6 @@ if __name__ == "__main__":
 
     heat_demand.index.name="snapshots"
 
-    print(heat_demand)
+    ds = heat_demand.stack().to_xarray()    
-
-    print(heat_demand.stack())
-
-    ds = heat_demand.stack().to_xarray()#xr.Dataset.from_dataframe(heat_demand)
-
-    print(ds)
 
     ds.to_netcdf(snakemake.output.heat_demand)

scripts/prepare_sector_network.py

@@ -1654,7 +1654,7 @@ def build_heat_demand(n):
         heat_demand[name] = (
             heat_demand_shape[name] / heat_demand_shape[name].sum()
         ).multiply(pop_weighted_energy_totals[f"total {sector} {use}"]) * 1e6
-        electric_heat_supply[f"{sector} {use}"] = (
+        electric_heat_supply[name] = (
             heat_demand_shape[name] / heat_demand_shape[name].sum()
         ).multiply(pop_weighted_energy_totals[f"electricity {sector} {use}"]) * 1e6