Merge remote-tracking branch 'origin/master'

romainsacchi · Apr 24, 2023 · 3175da9 · 3175da9
2 parents 0780f68 + 0c10eea
commit 3175da9
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Showing 5 changed files with 104 additions and 40 deletions.
diff --git a/carculator_bus/__init__.py b/carculator_bus/__init__.py
@@ -15,7 +15,7 @@
     "BusModel",
     "InventoryBus",
     "get_driving_cycle",
-    "get_road_gradient"
+    "get_road_gradient",
 )
 
 # library version
@@ -25,8 +25,9 @@
 
 DATA_DIR = Path(__file__).resolve().parent / "data"
 
+from carculator_utils.array import fill_xarray_from_input_parameters
+
 from .bus_input_parameters import BusInputParameters
+from .driving_cycles import get_driving_cycle, get_road_gradient
 from .inventory import InventoryBus
 from .model import BusModel
-from .driving_cycles import get_driving_cycle, get_road_gradient
-from carculator_utils.array import fill_xarray_from_input_parameters
diff --git a/carculator_bus/driving_cycles.py b/carculator_bus/driving_cycles.py
@@ -1,5 +1,5 @@
-from carculator_utils import get_standard_driving_cycle_and_gradient
 import numpy as np
+from carculator_utils import get_standard_driving_cycle_and_gradient
 
 
 def get_driving_cycle(size: list) -> np.ndarray:
@@ -15,4 +15,4 @@ def get_road_gradient(size: list) -> np.ndarray:
         vehicle_type="bus",
         vehicle_sizes=size,
         name="bus",
-    )[1]
+    )[1]
diff --git a/carculator_bus/inventory.py b/carculator_bus/inventory.py
@@ -350,7 +350,6 @@ def fill_in_A_matrix(self):
             ["BEV-depot", "PHEV-d"],
         )
 
-
         self.A[
             np.ix_(
                 np.arange(self.iterations),
@@ -359,9 +358,12 @@ def fill_in_A_matrix(self):
                     contains=("Bus, ", "battery"), excludes=("motion", "opp")
                 ),
             )
-        ] = -1 / (
-            self.array[self.array_inputs["kilometers per year"], :, index] * 2 * 24
-        ).values[:, None]
+        ] = (
+            -1
+            / (
+                self.array[self.array_inputs["kilometers per year"], :, index] * 2 * 24
+            ).values[:, None]
+        )
 
         # Opportunity charging BEV buses
         # The charging station has a lifetime of 24 years
@@ -380,9 +382,12 @@ def fill_in_A_matrix(self):
                 ),
                 self.find_input_indices(contains=("Bus, ", "BEV-opp")),
             )
-        ] = -1 / (
-            self.array[self.array_inputs["kilometers per year"], :, index] * 10 * 24
-        ).values[:, None]
+        ] = (
+            -1
+            / (
+                self.array[self.array_inputs["kilometers per year"], :, index] * 10 * 24
+            ).values[:, None]
+        )
 
         # In-motion charging BEV buses
         # The overhead lines have a lifetime of 40 years
@@ -399,8 +404,11 @@ def fill_in_A_matrix(self):
                 self.find_input_indices(("Overhead lines",)),
                 self.find_input_indices(contains=("Bus, ", "BEV-motion")),
             )
-        ] = -1 / (
-            self.array[self.array_inputs["lifetime kilometers"], :, index] * 60 * 40
-        ).values[:, None]
+        ] = (
+            -1
+            / (
+                self.array[self.array_inputs["lifetime kilometers"], :, index] * 60 * 40
+            ).values[:, None]
+        )
 
         print("*********************************************************************")
diff --git a/carculator_bus/model.py b/carculator_bus/model.py
@@ -394,7 +394,11 @@ def check_compliance_of_buses(self):
 
         if len(l_size) > 0:
             self.array.loc[
-                dict(powertrain="BEV-motion", parameter="is_available", size=l_size,)
+                dict(
+                    powertrain="BEV-motion",
+                    parameter="is_available",
+                    size=l_size,
+                )
             ] = 0
 
     def adjust_cost(self):
@@ -448,7 +452,13 @@ def adjust_cost(self):
         ]
 
         if len(l_pwt) > 0:
-            self.array.loc[:, l_pwt, "energy battery cost per kWh", :, :,] = np.reshape(
+            self.array.loc[
+                :,
+                l_pwt,
+                "energy battery cost per kWh",
+                :,
+                :,
+            ] = np.reshape(
                 (2.75e86 * np.exp(-9.61e-2 * self.array.year.values) + 5.059e1)
                 * cost_factor,
                 (1, 1, n_year, n_iterations),
@@ -462,7 +472,13 @@ def adjust_cost(self):
         ]
 
         if len(l_pwt) > 0:
-            self.array.loc[:, l_pwt, "power battery cost per kW", :, :,] = np.reshape(
+            self.array.loc[
+                :,
+                l_pwt,
+                "power battery cost per kW",
+                :,
+                :,
+            ] = np.reshape(
                 (8.337e40 * np.exp(-4.49e-2 * self.array.year.values) + 11.17)
                 * cost_factor,
                 (1, 1, n_year, n_iterations),
@@ -471,7 +487,11 @@ def adjust_cost(self):
         # Correction of combustion powertrain cost for ICEV-g
         if "ICEV-g" in self.array.powertrain.values:
             self.array.loc[
-                :, ["ICEV-g"], "combustion powertrain cost per kW", :, :,
+                :,
+                ["ICEV-g"],
+                "combustion powertrain cost per kW",
+                :,
+                :,
             ] = np.reshape(
                 (5.92e160 * np.exp(-0.1819 * self.array.year.values) + 26.76)
                 * cost_factor,
@@ -541,7 +561,9 @@ def calculate_ttw_energy(self):
                     "battery heating energy",
                     "recuperated energy",
                 ]
-            ).sum(dim=["second", "parameter"]).values
+            )
+            .sum(dim=["second", "parameter"])
+            .values
             / distance.values
         ).T
 
@@ -579,7 +601,9 @@ def calculate_ttw_energy(self):
                     "battery cooling energy",
                     "battery heating energy",
                 ]
-            ).sum(dim=["parameter", "second"]).values
+            )
+            .sum(dim=["parameter", "second"])
+            .values
             / distance.values
         ).T
 
@@ -734,7 +758,10 @@ def set_trips_properties(self):
         # (we omitted the stops in the average)
         speed = self.ecm.velocity / 1000 * 3600
         speed[speed == 0] = np.nan
-        self["average speed"] = np.nanmean(speed, axis=0,).T
+        self["average speed"] = np.nanmean(
+            speed,
+            axis=0,
+        ).T
         self["daily distance"] = self["operation time"] * self["average speed"]
 
         # the number of trips is simply the daily driven distance
@@ -799,7 +826,15 @@ def set_energy_stored_properties(self):
             )
 
             self.array.loc[dict(powertrain="FCEV", parameter="fuel tank mass")] = (
-                (-0.1916 * np.power(14.4, 2,)) + (14.586 * 14.4) + 10.805
+                (
+                    -0.1916
+                    * np.power(
+                        14.4,
+                        2,
+                    )
+                )
+                + (14.586 * 14.4)
+                + 10.805
             ) * nb_cylinder
 
         # for older trolley BEV buses,
@@ -994,14 +1029,11 @@ def set_energy_stored_properties(self):
 
             self.array.loc[
                 dict(powertrain="FCEV", parameter="electric energy stored")
-            ] = (
-                20
-                + (
-                    self.array.loc[dict(powertrain="FCEV", parameter="fuel mass")]
-                    * 120
-                    / 3.6
-                    * 0.06
-                )
+            ] = 20 + (
+                self.array.loc[dict(powertrain="FCEV", parameter="fuel mass")]
+                * 120
+                / 3.6
+                * 0.06
             )
 
         self["battery cell mass"] = self["electric energy stored"] / _(
@@ -1391,7 +1423,13 @@ def calculate_cost_impacts(self, sensitivity=False, scope=None):
             dims=["size", "powertrain", "cost_type", "year", "value"],
         )
 
-        response.loc[:, :, list_cost_cat, :, :,] = self.array.sel(
+        response.loc[
+            :,
+            :,
+            list_cost_cat,
+            :,
+            :,
+        ] = self.array.sel(
             powertrain=scope["powertrain"],
             size=scope["size"],
             year=scope["year"],
@@ -1420,28 +1458,43 @@ def remove_energy_consumption_from_unavailable_vehicles(self):
 
         pwts = [
             pt
-            for pt in ["BEV-depot", "BEV-opp", "BEV-motion",]
+            for pt in [
+                "BEV-depot",
+                "BEV-opp",
+                "BEV-motion",
+            ]
             if pt in self.array.coords["powertrain"].values
         ]
 
         years = [y for y in self.array.year.values if y < 2020]
 
         if years:
             self.array.loc[
-                dict(parameter="TtW energy", powertrain=pwts, year=years,)
+                dict(
+                    parameter="TtW energy",
+                    powertrain=pwts,
+                    year=years,
+                )
             ] = 0
 
         # and also coach buses with BEV-opp or BEV-motion powertrain
         pwts = [
             pt
-            for pt in ["BEV-opp", "BEV-motion",]
+            for pt in [
+                "BEV-opp",
+                "BEV-motion",
+            ]
             if pt in self.array.coords["powertrain"].values
         ]
         sizes = [s for s in self.array.coords["size"].values if "coach" in s.lower()]
 
         if pwts and sizes:
             self.array.loc[
-                dict(parameter="TtW energy", powertrain=pwts, size=sizes,)
+                dict(
+                    parameter="TtW energy",
+                    powertrain=pwts,
+                    size=sizes,
+                )
             ] = 0
 
         # remove double-deck BEV-motion buses
@@ -1466,4 +1519,4 @@ def remove_energy_consumption_from_unavailable_vehicles(self):
             < self["average passengers"] * 1.5,
             0,
             self["TtW energy"],
-        )
+        )
diff --git a/dev/mc_time.py b/dev/mc_time.py
@@ -1,11 +1,13 @@
 import pandas as pd
+
 from carculator_bus import *
+
 bip = BusInputParameters()
-#bip.stochastic(5)
+# bip.stochastic(5)
 bip.static()
 dcts, array = fill_xarray_from_input_parameters(
     bip,
-    scope={"year":[2020], "size":["9m","18m"], "powertrain":["BEV-motion"]},
+    scope={"year": [2020], "size": ["9m", "18m"], "powertrain": ["BEV-motion"]},
 )
 bm = BusModel(array, country="CH")
-bm.set_all()
+bm.set_all()