Merge remote-tracking branch 'origin/main'

.idea/costs.iml

@@ -2,7 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
+    <orderEntry type="jdk" jdkName="hub" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
   <component name="PyDocumentationSettings">

.idea/misc.xml

@@ -1,4 +1,4 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="costs_workflow" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="hub" project-jdk-type="Python SDK" />
 </project>

costs/total_operational_costs.py

@@ -11,6 +11,48 @@ from costs.configuration import Configuration
 from costs.cost_base import CostBase
 
 
+def Peak_load(building):
+  array = [None] * 12
+  heating = 0
+  cooling = 0
+  for system in building.energy_systems:
+    for demand_type in system.demand_types:
+      if demand_type == cte.HEATING:
+        heating = 1
+      if demand_type == cte.COOLING:
+        cooling = 1
+  if cte.MONTH in building.heating_peak_load.keys() and cte.MONTH in building.cooling_peak_load.keys():
+    peak_lighting = 0
+    peak_appliances = 0
+    for thermal_zone in building.internal_zones[0].thermal_zones:
+      lighting = thermal_zone.lighting
+      for schedule in lighting.schedules:
+        for value in schedule.values:
+          if value * lighting.density * thermal_zone.total_floor_area > peak_lighting:
+            peak_lighting = value * lighting.density * thermal_zone.total_floor_area
+      appliances = thermal_zone.appliances
+      for schedule in appliances.schedules:
+        for value in schedule.values:
+          if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
+            peak_appliances = value * appliances.density * thermal_zone.total_floor_area
+
+    monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
+    conditioning_peak = []
+    for i, value in enumerate(building.heating_peak_load[cte.MONTH]):
+      if cooling * building.cooling_peak_load[cte.MONTH][i] > heating * value:
+        conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][i])
+      else:
+        conditioning_peak.append(heating * value)
+      monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
+
+    electricity_peak_load_results = pd.DataFrame(monthly_electricity_peak
+                                                 , columns=[f'{building.name} electricity peak load W'])
+  else:
+    electricity_peak_load_results = pd.DataFrame(array, columns=[f'{building.name} electricity peak load W'])
+
+  return electricity_peak_load_results
+
+
 class TotalOperationalCosts(CostBase):
   """
   End of life costs class
@@ -29,6 +71,7 @@ class TotalOperationalCosts(CostBase):
       dtype='float'
     )
 
+
   def calculate(self) -> pd.DataFrame:
     """
     Calculate total operational costs
@@ -63,7 +106,9 @@ class TotalOperationalCosts(CostBase):
     )
 
     # todo: change when peak electricity demand is coded. Careful with factor residential
-    peak_electricity_demand = 100  # self._peak_electricity_demand
+    peak_electricity_load = Peak_load(building)
+    peak_load_value = peak_electricity_load.max(axis=1)
+    peak_electricity_demand = peak_load_value[1]/1000  # self._peak_electricity_demand adapted to kW
     variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0]
     peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12
     monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential

tests/unit_tests.py

@@ -20,8 +20,8 @@ from costs.constants import SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND
 
 class UnitTests(unittest.TestCase):
   def setUp(self) -> None:
-    city_file = Path("./tests/data/test.geojson").resolve()
+    city_file = Path("./data/test.geojson").resolve()
-    output_path = Path('./tests/output/').resolve()
+    output_path = Path('./output/').resolve()
     city = GeometryFactory('geojson',
                            city_file,
                            height_field='citygml_me',
@@ -32,7 +32,7 @@ class UnitTests(unittest.TestCase):
     UsageFactory('nrcan', city).enrich()
     ExportsFactory('sra', city, output_path).export()
     sra_file = str((output_path / f'{city.name}_sra.xml').resolve())
-    subprocess.run(['/usr/local/bin/sra', sra_file])
+    subprocess.run(['sra', sra_file])
     ResultFactory('sra', city, output_path).enrich()
 
     for building in city.buildings: