Feature/#359 add re energy share result

CHANGELOG.md

@@ -6,13 +6,14 @@ and this project tries to adhere to [Semantic Versioning](https://semver.org/spe
 
 ## [Unreleased]
 ### Added
-
+- RES share charts and choropleth for user scenario
 
 ### Changed
 
 
 ### Fixed
 - various fixes in charts, texts and units
+- RES share calculation for SQ
 
 ## [0.6.0] - 2023-09-01
 ### Added

config/settings/base.py

@@ -404,6 +404,12 @@ def __getitem__(self, item):  # noqa: D105, ANN001, ANN204
         title=_("Anteil Erneuerbare Energien am Strombedarf"),
         unit="%",
     ),
+    setup.Choropleth(
+        "energy_share_2045",
+        layers=["municipality"],
+        title=_("Anteil Erneuerbare Energien am Strombedarf"),
+        unit="%",
+    ),
     setup.Choropleth(
         "energy_capita_statusquo",
         layers=["municipality"],
@@ -510,6 +516,7 @@ def __getitem__(self, item):  # noqa: D105, ANN001, ANN204
             "energy_statusquo",
             "energy_2045",
             "energy_share_statusquo",
+            "energy_share_2045",
             "energy_capita_statusquo",
             "energy_capita_2045",
             "energy_square_statusquo",

digiplan/map/calculations.py

@@ -202,6 +202,25 @@ def energy_shares_per_municipality() -> pd.DataFrame:
     """
     Calculate energy shares of renewables from electric demand per municipality.
 
+    Returns
+    -------
+    pd.DataFrame
+        Energy share per municipality (index) and technology (column)
+    """
+    energies = energies_per_municipality()
+    demands = datapackage.get_power_demand()
+    total_demand = pd.concat([d["2022"] for d in demands.values()], axis=1).sum(axis=1)
+    energy_shares = energies.mul(1e3).div(total_demand, axis=0)
+    return energy_shares.mul(1e2)
+
+
+def energy_shares_region() -> pd.DataFrame:
+    """
+    Calculate energy shares of renewables from electric demand for region.
+
+    Like energy_shares_per_municipality() but with weighted demand for correct
+    totals.
+
     Returns
     -------
     pd.DataFrame
@@ -211,8 +230,8 @@ def energy_shares_per_municipality() -> pd.DataFrame:
     demands = datapackage.get_power_demand()
     total_demand = pd.concat([d["2022"] for d in demands.values()], axis=1).sum(axis=1)
     total_demand_share = total_demand / total_demand.sum()
-    energies = energies.reindex(range(20))
-    return energies.mul(total_demand_share, axis=0)
+    energy_shares = energies.mul(1e3).div(total_demand, axis=0).mul(total_demand_share, axis=0).sum(axis=0)
+    return energy_shares.mul(1e2)
 
 
 def electricity_demand_per_municipality(year: int = 2022) -> pd.DataFrame:
@@ -234,6 +253,41 @@ def electricity_demand_per_municipality(year: int = 2022) -> pd.DataFrame:
     return demands_per_sector * 1e-3
 
 
+def energy_shares_2045_per_municipality(simulation_id: int) -> pd.DataFrame:
+    """
+    Calculate energy shares of renewables from electric demand per municipality in 2045.
+
+    Returns
+    -------
+    pd.DataFrame
+        Energy share per municipality (index) and technology (column)
+    """
+    energies = energies_per_municipality_2045(simulation_id).mul(1e-3)
+    demands = electricity_demand_per_municipality_2045(simulation_id).sum(axis=1)
+    energy_shares = energies.div(demands, axis=0)
+    return energy_shares.astype(float).mul(1e2)
+
+
+def energy_shares_2045_region(simulation_id: int) -> pd.DataFrame:
+    """
+    Calculate energy shares of renewables from electric demand for region in 2045.
+
+    Like energy_shares_2045_per_municipality() but with weighted demand for
+    correct totals.
+
+    Returns
+    -------
+    pd.DataFrame
+        Energy share per municipality (index) and technology (column)
+    """
+    energies = energies_per_municipality_2045(simulation_id)
+    demands = electricity_demand_per_municipality_2045(simulation_id).sum(axis=1).mul(1e3)
+
+    demand_share = demands / demands.sum()
+    energy_shares = energies.div(demands, axis=0).mul(demand_share, axis=0).sum(axis=0)
+    return energy_shares.astype(float).mul(1e2)
+
+
 def electricity_demand_per_municipality_2045(simulation_id: int) -> pd.DataFrame:
     """
     Calculate electricity demand per sector per municipality in GWh in 2045.

digiplan/map/charts.py

@@ -487,13 +487,13 @@ def get_chart_options(self) -> dict:
 
 
 class EnergyShareRegionChart(Chart):
-    """Chart for regional energy shares."""
+    """Calculate RES energy shares for whole region."""
 
     lookup = "capacity"
 
     def get_chart_data(self) -> None:
         """Calculate capacities for whole region."""
-        return calculations.energy_shares_per_municipality().sum().round(1)
+        return calculations.energy_shares_region().round(1)
 
     def get_chart_options(self) -> dict:
         """Overwrite title and unit."""
@@ -503,6 +503,26 @@ def get_chart_options(self) -> dict:
         return chart_options
 
 
+class EnergyShare2045RegionChart(SimulationChart):
+    """Chart for regional energy shares."""
+
+    lookup = "capacity"
+
+    def get_chart_data(self) -> None:
+        """Calculate RES energy shares for whole region."""
+        status_quo_data = calculations.energy_shares_region().round(1)
+        future_data = calculations.energy_shares_2045_region(self.simulation_id).round(1)
+        return list(zip(status_quo_data, future_data))
+
+    def get_chart_options(self) -> dict:
+        """Overwrite title and unit."""
+        chart_options = super().get_chart_options()
+        del chart_options["title"]["text"]
+        chart_options["yAxis"]["name"] = _("%")
+        chart_options["xAxis"]["data"] = ["2022", "Dein\nSzenario"]
+        return chart_options
+
+
 class EnergyCapitaRegionChart(Chart):
     """Chart for regional energy shares per capita."""
 
@@ -956,6 +976,7 @@ def get_chart_options(self) -> dict:
     "energy_statusquo_region": EnergyRegionChart,
     "energy_2045_region": Energy2045RegionChart,
     "energy_share_statusquo_region": EnergyShareRegionChart,
+    "energy_share_2045_region": EnergyShare2045RegionChart,
     "energy_capita_statusquo_region": EnergyCapitaRegionChart,
     "energy_capita_2045_region": EnergyCapita2045RegionChart,
     "energy_square_statusquo_region": EnergySquareRegionChart,

digiplan/map/choropleths.py

@@ -79,7 +79,12 @@ def render(self) -> JsonResponse:
 
 class EnergyShareChoropleth(Choropleth):  # noqa: D101
     def get_values_per_feature(self) -> dict[int, float]:  # noqa: D102
-        return calculations.energy_shares_per_municipality().sum(axis=1).to_dict()
+        return calculations.energy_shares_per_municipality().sum(axis=1).round().to_dict()
+
+
+class EnergyShare2045Choropleth(Choropleth):  # noqa: D101
+    def get_values_per_feature(self) -> dict[int, float]:  # noqa: D102
+        return calculations.energy_shares_2045_per_municipality(self.map_state["simulation_id"]).sum(axis=1).to_dict()
 
 
 class EnergyChoropleth(Choropleth):  # noqa: D101
@@ -271,6 +276,7 @@ def get_values_per_feature(self) -> dict[int, float]:  # noqa: D102
     "energy_statusquo": EnergyChoropleth,
     "energy_2045": Energy2045Choropleth,
     "energy_share_statusquo": EnergyShareChoropleth,
+    "energy_share_2045": EnergyShare2045Choropleth,
     "energy_capita_statusquo": EnergyCapitaChoropleth,
     "energy_capita_2045": EnergyCapita2045Choropleth,
     "energy_square_statusquo": EnergySquareChoropleth,

digiplan/map/popups.py

@@ -336,7 +336,7 @@ class EnergySharePopup(RegionPopup):
     title = _("Anteil Energie aus EE")
 
     def get_detailed_data(self) -> pd.DataFrame:  # noqa: D102
-        return calculations.energy_shares_per_municipality()
+        return calculations.energy_shares_per_municipality().round(1)
 
     def get_chart_options(self) -> dict:
         """Overwrite title and unit."""
@@ -346,6 +346,30 @@ def get_chart_options(self) -> dict:
         return chart_options
 
 
+class EnergyShare2045Popup(RegionPopup):
+    """Popup to show energy shares."""
+
+    lookup = "capacity"
+    title = _("Anteil Energie aus EE")
+
+    def get_detailed_data(self) -> pd.DataFrame:  # noqa: D102
+        return calculations.energy_shares_2045_per_municipality(self.map_state["simulation_id"])
+
+    def get_chart_options(self) -> dict:
+        """Overwrite title and unit."""
+        chart_options = super().get_chart_options()
+        chart_options["title"]["text"] = _("Energieanteile pro Technologie")
+        chart_options["yAxis"]["name"] = _("%")
+        chart_options["xAxis"]["data"] = ["2022", "Dein Szenario"]
+        return chart_options
+
+    def get_chart_data(self) -> Iterable:
+        """Create capacity chart data for SQ and future scenario."""
+        status_quo_data = calculations.energy_shares_per_municipality().loc[self.selected_id].round(1)
+        future_data = super().get_chart_data().round(1)
+        return list(zip(status_quo_data, future_data))
+
+
 class EnergyCapitaPopup(RegionPopup):
     """Popup to show energy shares per population."""
 
@@ -885,6 +909,7 @@ def get_chart_options(self) -> dict:
     "energy_statusquo": EnergyPopup,
     "energy_2045": Energy2045Popup,
     "energy_share_statusquo": EnergySharePopup,
+    "energy_share_2045": EnergyShare2045Popup,
     "energy_capita_statusquo": EnergyCapitaPopup,
     "energy_capita_2045": EnergyCapita2045Popup,
     "energy_square_statusquo": EnergySquarePopup,

digiplan/templates/components/panel_3_results.html

@@ -32,7 +32,7 @@ <h2 class="panel-item__heading panel-item__heading--nopadding">
       <select id="result_views" class="form-select" aria-label="Default select example">
         <option value="" title="{% translate "Keine Auswahl" %}" selected>{% translate "Keine Auswahl" %}</option>
         <optgroup label="{% translate "Renewable Energies (RE)" %}">
-          <option value="re_power_percentage"
+          <option value="energy_share_2045"
                   title="{% translate "Annual balance sheet share of renewable energy (wind energy, photovoltaic, hydroelectric power) in the electricity demand of the sectors agriculture, GHG (trade, commerce, services), households and industry in percent. The demand is the net electricity consumption, i.e. transmission losses and power plant consumption are not taken into account. 49.7% of the electricity demand in Germany was covered by renewable energies in 2022." %}">
                   {% translate "Renewable Energy Share of Demand" %} (%)
           </option>