feat: add support for europe_tub grid model in plotting functions

docs/code/curtailment_eastern.py

@@ -1,4 +1,4 @@
-import matplotlib.pyplot as plt
+from matplotlib import pyplot as plt
 from powersimdata import Scenario
 
 from postreise.plot.plot_curtailment_ts import plot_curtailment_time_series

postreise/analyze/generation/emissions.py

@@ -1,7 +1,6 @@
 import numpy as np
 import pandas as pd
 from powersimdata.input.check import _check_grid_type, _check_time_series
-from powersimdata.network.model import ModelImmutables
 from powersimdata.scenario.check import _check_scenario_is_in_analyze_state
 
 from postreise.analyze.generation.costs import calculate_costs
@@ -24,7 +23,7 @@ def generate_emissions_stats(scenario, pollutant="carbon", method="simple"):
           are off (detected by pg < 1 MW).
     """
     _check_scenario_is_in_analyze_state(scenario)
-    mi = ModelImmutables(scenario.info["grid_model"])
+    mi = scenario.get_grid().model_immutables
     allowed_methods = {
         "carbon": {"simple", "always-on", "decommit"},
         "nox": {"simple"},
@@ -124,7 +123,15 @@ def carbon_diff(scenario_1, scenario_2):
         generate_emissions_stats(scenario_2), scenario_2.get_grid()
     )
 
-    sum_1 = sum(carbon_by_bus_1["coal"].values()) + sum(carbon_by_bus_1["ng"].values())
-    sum_2 = sum(carbon_by_bus_2["coal"].values()) + sum(carbon_by_bus_2["ng"].values())
+    grid = scenario_1.state.get_grid()
+    coal_resource_types = grid.model_immutables.plants["group_all_resources"]["coal"]
+    ng_resource_types = grid.model_immutables.plants["group_all_resources"]["ng"]
+    resource_types = coal_resource_types.union(ng_resource_types)
+
+    sum_1 = 0
+    sum_2 = 0
+    for rtype in resource_types:
+        sum_1 = sum_1 + sum(carbon_by_bus_1[rtype].values())
+        sum_2 = sum_2 + sum(carbon_by_bus_2[rtype].values())
 
     return 100 * (1 - sum_2 / sum_1)

postreise/analyze/generation/summarize.py

@@ -50,6 +50,8 @@ def sum_generation_by_state(scenario: Scenario) -> pd.DataFrame:
     totals for the interconnects and for all states.
 
     :param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
+    :raises ValueError:
+        if grid model is not supported.
     :return: (*pandas.DataFrame*) -- total generation per resource, by area.
     """
     # Start with energy by type & zone name
@@ -59,8 +61,14 @@ def sum_generation_by_state(scenario: Scenario) -> pd.DataFrame:
     energy_by_type_zonename = energy_by_type_zoneid.rename(zoneid2zonename, axis=1)
     # Build lists to use for groupbys
     zone_list = energy_by_type_zonename.columns
+    if grid.grid_model == "usa_tamu":
+        loadzone2area = "loadzone2state"
+    elif grid.grid_model == "europe_tub":
+        loadzone2area = "loadzone2country"
+    else:
+        raise ValueError("grid model is not supported")
     zone_states = [
-        grid.model_immutables.zones["loadzone2state"][zone] for zone in zone_list
+        grid.model_immutables.zones[loadzone2area][zone] for zone in zone_list
     ]
     zone_interconnects = [
         grid.model_immutables.zones["loadzone2interconnect"][zone] for zone in zone_list

postreise/analyze/generation/tests/test_emissions.py

@@ -100,7 +100,6 @@ def test_method_value(self, scenario):
 
 class TestCarbonCalculation:
     def test_carbon_calc_always_on(self, scenario, mock_plant):
-
         carbon = generate_emissions_stats(scenario, method="always-on")
         _test_emissions_structure(carbon, mock_plant, scenario.state.get_pg())
 
@@ -118,7 +117,6 @@ def test_carbon_calc_always_on(self, scenario, mock_plant):
         )
 
     def test_carbon_calc_decommit(self, scenario, mock_plant):
-
         carbon = generate_emissions_stats(scenario, method="decommit")
         _test_emissions_structure(carbon, mock_plant, scenario.state.get_pg())
 
@@ -136,7 +134,6 @@ def test_carbon_calc_decommit(self, scenario, mock_plant):
         )
 
     def test_carbon_calc_simple(self, scenario, mock_plant):
-
         carbon = generate_emissions_stats(scenario, method="simple")
         _test_emissions_structure(carbon, mock_plant, scenario.state.get_pg())
 

postreise/plot/colors.py

@@ -31,3 +31,18 @@
     "red",
     "darkred",
 ]
+
+grid_colors = {
+    "usa_tamu": {
+        "Western": be_blue,
+        "Eastern": be_purple,
+        "Texas": be_lightblue,
+    },
+    "europe_tub": {
+        "ContinentalEurope": be_blue,
+        "Baltic": "#fed53d",
+        "Nordic": be_lightblue,
+        "GreatBritain": be_purple,
+        "Ireland": be_green,
+    },
+}

postreise/plot/plot_bar_generation_max_min_actual.py

@@ -1,5 +1,5 @@
-import matplotlib.pyplot as plt
 import pandas as pd
+from matplotlib import pyplot as plt
 from powersimdata.input.check import _check_resources_are_in_grid_and_format
 
 from postreise.analyze.generation.summarize import (
@@ -35,7 +35,9 @@ def plot_bar_generation_max_min_actual(
     :raises TypeError:
         if ``interconnect`` and ``gen_type`` are not str
         if ``fontsize`` is not an integer or a float and/or
-    :raises ValueError: if ``interconnect`` is not valid
+    :raises ValueError:
+        if ``interconnect`` is not valid
+        if grid model is not supported.
     """
     if not isinstance(interconnect, str):
         raise TypeError("interconnect must be a str")
@@ -53,26 +55,26 @@ def plot_bar_generation_max_min_actual(
         raise ValueError(
             f"interconnect must be one of {sorted(mi.zones['interconnect'])}"
         )
-    if (
-        len(
-            mi.zones["interconnect2abv"][interconnect]
-            - mi.zones["interconnect2abv"][scenario.info["interconnect"]]
-        )
-        != 0
-    ):
-        raise ValueError("interconnect is incompatible with scenario's interconnect")
 
     hour_num = (
         pd.Timestamp(scenario.info["end_date"])
         - pd.Timestamp(scenario.info["start_date"])
     ).total_seconds() / 3600 + 1
     if show_as_state:
+        if grid.grid_model == "usa_tamu":
+            abv2area = "abv2state"
+            loadzone2area = "loadzone2state"
+        elif grid.grid_model == "europe_tub":
+            abv2area = "abv2country"
+            loadzone2area = "loadzone2country"
+        else:
+            raise ValueError("grid model is not supported")
         zone_list = [
-            mi.zones["abv2state"][abv]
+            mi.zones[abv2area][abv]
             for abv in mi.zones["interconnect2abv"][interconnect]
         ]
         all_max_min = (
-            plant.groupby(plant.zone_name.map(mi.zones["loadzone2state"]))[
+            plant.groupby(plant.zone_name.map(mi.zones[loadzone2area]))[
                 ["Pmax", "Pmin"]
             ].sum()
             * hour_num

postreise/plot/plot_bar_generation_stack.py

@@ -1,8 +1,8 @@
 import os
 
-import matplotlib.pyplot as plt
 import pandas as pd
-from powersimdata.network.model import ModelImmutables, area_to_loadzone
+from matplotlib import pyplot as plt
+from powersimdata.network.model import area_to_loadzone
 from powersimdata.scenario.scenario import Scenario
 
 from postreise.analyze.generation.curtailment import (
@@ -95,7 +95,10 @@ def plot_bar_generation_stack(
     s_list = []
     for sid in scenario_ids:
         s_list.append(Scenario(sid))
-    mi = ModelImmutables(s_list[0].info["grid_model"])
+    mi = s_list[0].state.get_grid().model_immutables
+    # TODO: fix in mi
+    mi.plants["curtailable2color"]["offwind-dc"] = "#74c6f2"
+
     type2color = mi.plants["type2color"]
     type2color.update(
         {k + "_curtailment": v for k, v in mi.plants["curtailable2color"].items()}
@@ -116,13 +119,14 @@ def plot_bar_generation_stack(
 
     all_loadzone_data = dict()
     for sid, scenario in zip(scenario_ids, s_list):
+        if scenario.info["interconnect"] in ["USA", "Europe"]:
+            loadzones = mi.zones["loadzone"]
+        else:
+            loadzones = mi.zones["interconnect2loadzone"][scenario.info["interconnect"]]
+
         curtailment = calculate_curtailment_time_series_by_areas_and_resources(
             scenario,
-            areas={
-                "loadzone": mi.zones["interconnect2loadzone"][
-                    scenario.info["interconnect"]
-                ]
-            },
+            areas={"loadzone": loadzones},
         )
         for area in curtailment:
             for r in curtailment[area]:

postreise/plot/plot_bar_generation_vs_capacity.py

@@ -1,6 +1,6 @@
-import matplotlib.pyplot as plt
 import pandas as pd
-from powersimdata.network.model import ModelImmutables, area_to_loadzone
+from matplotlib import pyplot as plt
+from powersimdata.network.model import area_to_loadzone
 from powersimdata.scenario.scenario import Scenario
 
 from postreise.analyze.generation.capacity import sum_capacity_by_type_zone
@@ -83,7 +83,7 @@ def plot_bar_generation_vs_capacity(
     scenario_data = {}
     for i, sid in enumerate(scenario_ids):
         scenario = Scenario(sid)
-        mi = ModelImmutables(scenario.info["grid_model"])
+        mi = scenario.state.get_grid().model_immutables
         all_loadzone_data[sid] = {
             "gen": sum_generation_by_type_zone(scenario, time_range, time_zone).rename(
                 columns=mi.zones["id2loadzone"]

postreise/plot/plot_bar_renewable_max_profile_actual.py

@@ -1,5 +1,5 @@
-import matplotlib.pyplot as plt
 import pandas as pd
+from matplotlib import pyplot as plt
 from powersimdata.input.check import (
     _check_resources_are_in_grid_and_format,
     _check_resources_are_renewable_and_format,
@@ -58,14 +58,6 @@ def plot_bar_renewable_max_profile_actual(
         raise ValueError(
             f"interconnect must be one of {sorted(mi.zones['interconnect'])}"
         )
-    if (
-        len(
-            mi.zones["interconnect2abv"][interconnect]
-            - mi.zones["interconnect2abv"][scenario.info["interconnect"]]
-        )
-        != 0
-    ):
-        raise ValueError("interconnect is incompatible with scenario's interconnect")
 
     if "wind" in gen_type:
         profile = scenario.get_wind().sum()
@@ -76,11 +68,19 @@ def plot_bar_renewable_max_profile_actual(
         - pd.Timestamp(scenario.info["start_date"])
     ).total_seconds() / 3600 + 1
     if show_as_state:
+        if grid.grid_model == "usa_tamu":
+            abv2area = "abv2state"
+            loadzone2area = "loadzone2state"
+        elif grid.grid_model == "europe_tub":
+            abv2area = "abv2country"
+            loadzone2area = "loadzone2country"
+        else:
+            raise ValueError("grid model is not supported")
         zone_list = [
-            mi.zones["abv2state"][abv]
+            mi.zones[abv2area][abv]
             for abv in mi.zones["interconnect2abv"][interconnect]
         ]
-        group_criteria = plant.zone_name.map(mi.zones["loadzone2state"])
+        group_criteria = plant.zone_name.map(mi.zones[loadzone2area])
         profile_gen = profile.groupby(group_criteria).sum().rename("profile")
         total_capacity = plant.groupby(group_criteria)["Pmax"].sum() * hour_num
         actual_gen = sum_generation_by_state(scenario)[gen_type] * 1000

postreise/plot/plot_bar_shortfall.py

@@ -1,5 +1,5 @@
-import matplotlib.pyplot as plt
 import pandas as pd
+from matplotlib import pyplot as plt
 from powersimdata.design.generation.clean_capacity_scaling import (
     add_demand_to_targets,
     add_resource_data_to_targets,